Publications

Preprints

• Beyond Accuracy and Cost: Latency-Aware LLM Query Routing for Dynamic Workloads
  Shivam Patel, Akaash Parthasarathy, Ankur Mallick, and Gauri Joshi
  preprint
  arXiv

  BibTeX

  @misc{patel2026beyond,
    author = {Shivam Patel and Akaash Parthasarathy and Ankur Mallick and Gauri Joshi},
    title  = {{Beyond Accuracy and Cost: Latency-Aware LLM Query Routing for Dynamic Workloads}},
    year   = {2026},
    url    = {https://arxiv.org/abs/2607.18253}
  }

• Emergent and Subliminal Misalignment Through the Lens of Data-Mediated Transfer
  Baris Askin, Muhammed Ustaomeroglu, Anupam Nayak, Gauri Joshi, Guannan Qu, and Carlee Joe-Wong
  preprint
  arXiv

  BibTeX

  @misc{askin2026emergent,
    author = {Baris Askin and Muhammed Ustaomeroglu and Anupam Nayak and Gauri Joshi and Guannan Qu and Carlee Joe-Wong},
    title  = {{Emergent and Subliminal Misalignment Through the Lens of Data-Mediated Transfer}},
    year   = {2026},
    url    = {https://arxiv.org/abs/2605.12798}
  }

• Not All Turns Are Equally Hard: Adaptive Thinking Budgets For Efficient Multi-Turn Reasoning
  Neharika Jali, Anupam Nayak, and Gauri Joshi
  preprint
  arXiv

  BibTeX

  @misc{jali2026not,
    author = {Neharika Jali and Anupam Nayak and Gauri Joshi},
    title  = {{Not All Turns Are Equally Hard: Adaptive Thinking Budgets For Efficient Multi-Turn Reasoning}},
    year   = {2026},
    url    = {https://arxiv.org/abs/2604.05164}
  }

• Federate the Router: Learning Language Model Routers with Sparse and Decentralized Evaluations
  Baris Askin, Shivam Patel, Anupam Nayak, Andrea Vigano, Jiin Woo, Gauri Joshi, and Carlee Joe-Wong
  preprint
  arXiv

  BibTeX

  @misc{askin2026federate,
    author = {Baris Askin and Shivam Patel and Anupam Nayak and Andrea Vigano and Jiin Woo and Gauri Joshi and Carlee Joe-Wong},
    title  = {{Federate the Router: Learning Language Model Routers with Sparse and Decentralized Evaluations}},
    year   = {2026},
    url    = {https://www.arxiv.org/abs/2601.22318}
  }

• MELINOE: Fine-Tuning Enables Memory-Efficient Inference for Mixture-of-Experts Models
  Arian Raje, Anupam Nayak, and Gauri Joshi
  preprint
  arXiv

  BibTeX

  @misc{raje2026melinoe,
    author = {Arian Raje and Anupam Nayak and Gauri Joshi},
    title  = {{MELINOE: Fine-Tuning Enables Memory-Efficient Inference for Mixture-of-Experts Models}},
    year   = {2026},
    url    = {https://arxiv.org/pdf/2602.11192}
  }

• Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning
  Baris Askin, Holger R. Roth, Zhenyu Sun, Carlee Joe-Wong, Gauri Joshi, and Ziyue Xu
  preprint
  arXiv

  BibTeX

  @misc{askin2026reviving,
    author = {Baris Askin and Holger R. Roth and Zhenyu Sun and Carlee Joe-Wong and Gauri Joshi and Ziyue Xu},
    title  = {{Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning}},
    year   = {2026},
    url    = {https://arxiv.org/abs/2511.00655}
  }

• Sample Complexity of Average-Reward Q-Learning: From Single-agent to Federated Reinforcement Learning
  Yuchen Jiao, Jiin Woo, Gen Li, Gauri Joshi, and Yuejie Chi
  preprint
  arXiv

  BibTeX

  @misc{jiao2026sample,
    author = {Yuchen Jiao and Jiin Woo and Gen Li and Gauri Joshi and Yuejie Chi},
    title  = {{Sample Complexity of Average-Reward Q-Learning: From Single-agent to Federated Reinforcement Learning}},
    year   = {2026},
    url    = {https://arxiv.org/abs/2601.13642}
  }

• FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
  Divyansh Jhunjhunwala, Arian Raje, Madan Ravi Ganesh, Chaithanya Kumar Mummadi, Chaoqun Dong, Jiawei Zhou, Wan-Yi Lin, Gauri Joshi, and Zhenzhen Li
  preprint
  arXiv

  BibTeX

  @misc{jhunjhunwala2026fedrpca,
    author = {Divyansh Jhunjhunwala and Arian Raje and Madan Ravi Ganesh and Chaithanya Kumar Mummadi and Chaoqun Dong and Jiawei Zhou and Wan-Yi Lin and Gauri Joshi and Zhenzhen Li},
    title  = {{FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA}},
    year   = {2026},
    url    = {https://arxiv.org/abs/2506.01194}
  }

2026

• Low-Dimensional Model Embeddings for Efficient Model Exploration, Comparison and Selection
  Shivam Patel, William Cocke, and Gauri Joshi
  Proceedings of the AdaptFM workshop at the International Conference on Machine Learning (ICML) 2026
  arXiv

  BibTeX

  @inproceedings{patel2026lowdimensional,
    author    = {Shivam Patel and William Cocke and Gauri Joshi},
    title     = {{Low-Dimensional Model Embeddings for Efficient Model Exploration, Comparison and Selection}},
    booktitle = {Proceedings of the AdaptFM workshop at the International Conference on Machine Learning (ICML) 2026},
    year      = {2026},
    url       = {https://arxiv.org/abs/2601.21082}
  }

• PubSwap: Public-Data Off-Policy Coordination for Federated RLVR
  Anupam Nayak, Baris Askin, Muhammed Ustaomeroglu, Carlee Joe-Wong, and Gauri Joshi
  Proceedings of the RLxF and DEMO workshops at the International Conference on Machine Learning (ICML) 2026
  arXiv

  BibTeX

  @inproceedings{nayak2026pubswap,
    author    = {Anupam Nayak and Baris Askin and Muhammed Ustaomeroglu and Carlee Joe-Wong and Gauri Joshi},
    title     = {{PubSwap: Public-Data Off-Policy Coordination for Federated RLVR}},
    booktitle = {Proceedings of the RLxF and DEMO workshops at the International Conference on Machine Learning (ICML) 2026},
    year      = {2026},
    url       = {https://arxiv.org/abs/2604.12160}
  }

• Adaptive Federated Learning via Dynamical System Model
  Aayushya Agarwal, Gauri Joshi, and Larry Pileggi
  Transactions of Machine Learning Research, May 2026
  shorter version appeared in the Proceedings of the NeurIPS DynaFront workshop, Dec 2025
  arXiv

  BibTeX

  @article{agarwal2026adaptive,
    author  = {Aayushya Agarwal and Gauri Joshi and Larry Pileggi},
    title   = {{Adaptive Federated Learning via Dynamical System Model}},
    journal = {Transactions of Machine Learning Research},
    year    = {2026},
    month   = {5},
    url     = {https://arxiv.org/abs/2510.04203}
  }

• The Cost of Shuffling in Private Gradient-Based Optimization
  Shuli Jiang, Pranay Sharma, Steven Wu, and Gauri Joshi
  Conference on Uncertainty in Artificial Intelligence (UAI) 2026
  arXiv

  BibTeX

  @inproceedings{jiang2026the,
    author    = {Shuli Jiang and Pranay Sharma and Steven Wu and Gauri Joshi},
    title     = {{The Cost of Shuffling in Private Gradient-Based Optimization}},
    booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI) 2026},
    year      = {2026},
    url       = {https://arxiv.org/abs/2502.03652}
  }

• Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games
  Anupam Nayak, Tong Yang, Osman Yagan, Gauri Joshi, and Yuejie Chi
  International Conference on Machine Learning (ICML), July 2026
  arXiv

  BibTeX

  @inproceedings{nayak2026achieving,
    author    = {Anupam Nayak and Tong Yang and Osman Yagan and Gauri Joshi and Yuejie Chi},
    title     = {{Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2026},
    month     = {7},
    url       = {https://www.arxiv.org/abs/2510.13060}
  }

• Federated Learning is a Lens towards a Democratized Future for the Scaling Law Era
  Harry Jiang, Baris Askin, Gauri Joshi, and Carlee Joe-Wong
  International Conference on Machine Learning (ICML) position paper, July 2026
  BibTeX

  @inproceedings{jiang2026federated,
    author    = {Harry Jiang and Baris Askin and Gauri Joshi and Carlee Joe-Wong},
    title     = {{Federated Learning is a Lens towards a Democratized Future for the Scaling Law Era}},
    booktitle = {International Conference on Machine Learning (ICML) position paper},
    year      = {2026},
    month     = {7}
  }

• ProxRouter: Proximity-Weighted LLM Query Routing for Improved Robustness to Outliers
  Shivam Patel, Neharika Jali, Ankur Mallick, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2026
  arXiv

  BibTeX

  @inproceedings{patel2026proxrouter,
    author    = {Shivam Patel and Neharika Jali and Ankur Mallick and Gauri Joshi},
    title     = {{ProxRouter: Proximity-Weighted LLM Query Routing for Improved Robustness to Outliers}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2026},
    month     = {5},
    url       = {https://arxiv.org/abs/2510.09852}
  }

• Internal Planning in Language Models: Characterizing Horizon and Branch Awareness
  Muhammed Ustaomeroglu, Baris Askin, Gauri Joshi, Carlee Joe-Wong, and Guannan Qu
  International Conference on Learning Representations (ICLR), Apr 2026
  short version presented at the DeepMath Conference on the Mathematical Theory of Deep Neural Networks, Nov 2025
  arXiv

  BibTeX

  @inproceedings{ustaomeroglu2026internal,
    author    = {Muhammed Ustaomeroglu and Baris Askin and Gauri Joshi and Carlee Joe-Wong and Guannan Qu},
    title     = {{Internal Planning in Language Models: Characterizing Horizon and Branch Awareness}},
    booktitle = {International Conference on Learning Representations (ICLR)},
    year      = {2026},
    month     = {4},
    url       = {https://arxiv.org/abs/2509.25260}
  }

• Navigating the Accuracy-Size Trade-Off with Flexible Model Merging
  Akash Dhasade, Divyansh Jhunjhunwala, Milos Vujasinovic, Gauri Joshi, and Anne-Marie Kermarrec
  International Conference on Learning Representations (ICLR), Apr 2026
  arXiv

  BibTeX

  @inproceedings{dhasade2026navigating,
    author    = {Akash Dhasade and Divyansh Jhunjhunwala and Milos Vujasinovic and Gauri Joshi and Anne-Marie Kermarrec},
    title     = {{Navigating the Accuracy-Size Trade-Off with Flexible Model Merging}},
    booktitle = {International Conference on Learning Representations (ICLR)},
    year      = {2026},
    month     = {4},
    url       = {https://arxiv.org/abs/2505.23209}
  }

• Natural Policy Gradient for Average Reward Non-Stationary RL
  Neharika Jali, Eshika Pathak, Pranay Sharma, Guannan Qu, and Gauri Joshi
  Transactions on Machine Learning Research (TMLR), Jan 2026
  TMLR 2026arXiv

  BibTeX

  @article{jali2026natural,
    author  = {Neharika Jali and Eshika Pathak and Pranay Sharma and Guannan Qu and Gauri Joshi},
    title   = {{Natural Policy Gradient for Average Reward Non-Stationary RL}},
    journal = {Transactions on Machine Learning Research (TMLR)},
    year    = {2026},
    month   = {1},
    url     = {https://arxiv.org/abs/2504.16415}
  }

2025

• Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning
  Arian Raje, Baris Askin, Divyansh Jhunjhunwala, and Gauri Joshi
  Neural Information Processing Systems (NeurIPS), Dec 2025
  NeurIPS 2025arXiv

  BibTeX

  @inproceedings{raje2025ravan,
    author    = {Arian Raje and Baris Askin and Divyansh Jhunjhunwala and Gauri Joshi},
    title     = {{Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning}},
    booktitle = {Neural Information Processing Systems (NeurIPS)},
    year      = {2025},
    month     = {12},
    url       = {https://www.arxiv.org/abs/2506.05568}
  }

• Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning
  Divyansh Jhunjhunwala, Pranay Sharma, Zheng Xu, and Gauri Joshi
  Transactions on Machine Learning Research (TMLR), Oct 2025
  TMLR 2025arXiv

  BibTeX

  @article{jhunjhunwala2025initialization,
    author  = {Divyansh Jhunjhunwala and Pranay Sharma and Zheng Xu and Gauri Joshi},
    title   = {{Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning}},
    journal = {Transactions on Machine Learning Research (TMLR)},
    year    = {2025},
    month   = {10},
    url     = {https://arxiv.org/abs/2502.08024}
  }

• FedECADO: A Dynamical System Model of Federated Learning
  Aayushya Agarwal, Gauri Joshi, and Larry Pileggi
  International Conference on Machine Learning (ICML), July 2025
  ICML 2025arXiv

  BibTeX

  @inproceedings{agarwal2025fedecado,
    author    = {Aayushya Agarwal and Gauri Joshi and Larry Pileggi},
    title     = {{FedECADO: A Dynamical System Model of Federated Learning}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2025},
    month     = {7},
    url       = {https://arxiv.org/abs/2410.09933}
  }

• Federated Communication-Efficient Multi-Objective Optimization
  Baris Askin, Pranay Sharma, Carlee Joe-Wong, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025
  AISTATS 2025arXiv

  BibTeX

  @inproceedings{askin2025federated,
    author    = {Baris Askin and Pranay Sharma and Carlee Joe-Wong and Gauri Joshi},
    title     = {{Federated Communication-Efficient Multi-Objective Optimization}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2025},
    month     = {5},
    url       = {https://arxiv.org/abs/2410.16398}
  }

• High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise
  Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, and Soummya Kar
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025
  AISTATS 2025arXiv

  BibTeX

  @inproceedings{armacki2025highprobability,
    author    = {Aleksandar Armacki and Shuhua Yu and Pranay Sharma and Gauri Joshi and Dragana Bajovic and Dusan Jakovetic and Soummya Kar},
    title     = {{High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2025},
    month     = {5},
    url       = {https://arxiv.org/abs/2310.18784}
  }

• Debiasing Federated Learning with Correlated Client Participation
  Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, and Ermin Wei
  International Conference on Learning Representations (ICLR), Apr 2025
  ICLR 2025arXiv

  BibTeX

  @inproceedings{sun2025debiasing,
    author    = {Zhenyu Sun and Ziyang Zhang and Zheng Xu and Gauri Joshi and Pranay Sharma and Ermin Wei},
    title     = {{Debiasing Federated Learning with Correlated Client Participation}},
    booktitle = {International Conference on Learning Representations (ICLR)},
    year      = {2025},
    month     = {4},
    url       = {https://arxiv.org/abs/2410.01209}
  }

• The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond
  Jiin Woo, Gauri Joshi, and Yuejie Chi
  Journal on Machine Learning Research (JMLR), Feb 2025
  JMLR 2025arXiv

  BibTeX

  @article{woo2025the,
    author  = {Jiin Woo and Gauri Joshi and Yuejie Chi},
    title   = {{The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond}},
    journal = {Journal on Machine Learning Research (JMLR)},
    year    = {2025},
    month   = {2},
    url     = {https://arxiv.org/abs/2305.10697}
  }

2024

• Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees
  Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, and Soummya Kar
  preprint
  arXiv

  BibTeX

  @misc{armacki2024nonlinear,
    author = {Aleksandar Armacki and Shuhua Yu and Pranay Sharma and Gauri Joshi and Dragana Bajovic and Dusan Jakovetic and Soummya Kar},
    title  = {{Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees}},
    year   = {2024},
    url    = {https://arxiv.org/abs/2410.13954}
  }

• Job Assignment in Machine Learning Inference Systems with Accuracy Constraints
  Tuhinangshu Choudhury, Weina Wang, and Gauri Joshi
  Performance Evaluation Journal, Elsevier, Dec 2024
  paper

  BibTeX

  @article{choudhury2024job,
    author  = {Tuhinangshu Choudhury and Weina Wang and Gauri Joshi},
    title   = {{Job Assignment in Machine Learning Inference Systems with Accuracy Constraints}},
    journal = {Performance Evaluation Journal, Elsevier},
    year    = {2024},
    month   = {12},
    url     = {https://www.sciencedirect.com/science/article/pii/S0166531624000683}
  }

• Optimized Tradeoffs for Private Majority Ensembling
  Shuli Jiang, Qiuyu Zhang, and Gauri Joshi
  Transaction on Machine Learning Research (TMLR), 2024
  TMLR 2024arXiv

  BibTeX

  @misc{jiang2024optimized,
    author       = {Shuli Jiang and Qiuyu Zhang and Gauri Joshi},
    title        = {{Optimized Tradeoffs for Private Majority Ensembling}},
    howpublished = {Transaction on Machine Learning Research (TMLR), 2024},
    year         = {2024},
    url          = {https://arxiv.org/abs/2411.17965}
  }

• Heterogeneous LoRA for Federated Fine-tuning of On-device Foundation Models
  Yae Jee Cho, Luyang Liu, Zheng Xu, Aldi Fahrezi, Matt Barnes, and Gauri Joshi
  Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov 2024
  shorter version in Workshop on Federated Learning in the Age of Foundation Models, Neural Information Processing Systems (NeurIPS), Dec 2023
  EMNLP 2024arXiv

  BibTeX

  @inproceedings{cho2024heterogeneous,
    author    = {Yae Jee Cho and Luyang Liu and Zheng Xu and Aldi Fahrezi and Matt Barnes and Gauri Joshi},
    title     = {{Heterogeneous LoRA for Federated Fine-tuning of On-device Foundation Models}},
    booktitle = {Conference on Empirical Methods in Natural Language Processing (EMNLP)},
    year      = {2024},
    month     = {11},
    url       = {https://arxiv.org/abs/2401.06432}
  }

• Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices
  Jiin Woo, Laixi Shi, Gauri Joshi, and Yuejie Chi
  International Conference on Machine Learning (ICML), July 2024
  ICML 2024arXiv

  BibTeX

  @inproceedings{woo2024federated,
    author    = {Jiin Woo and Laixi Shi and Gauri Joshi and Yuejie Chi},
    title     = {{Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2024},
    month     = {7},
    url       = {https://arxiv.org/abs/2402.05876}
  }

• FedAST: Federated Asynchronous Simultaneous Training
  Baris Askin, Pranay Sharma, Carlee Joe-Wong, and Gauri Joshi
  Conference on Uncertainty in Artificial Intelligence (UAI), July 2024
  UAI 2024arXiv

  BibTeX

  @inproceedings{askin2024fedast,
    author    = {Baris Askin and Pranay Sharma and Carlee Joe-Wong and Gauri Joshi},
    title     = {{FedAST: Federated Asynchronous Simultaneous Training}},
    booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
    year      = {2024},
    month     = {7},
    url       = {https://arxiv.org/abs/2406.00302}
  }

• Erasure Coded Neural Network Inference via Fisher Averaging
  Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, and Shiqiang Wang
  International Symposium on Information Theory (ISIT), July 2024
  ISIT 2024arXiv

  BibTeX

  @inproceedings{jhunjhunwala2024erasure,
    author    = {Divyansh Jhunjhunwala and Neharika Jali and Gauri Joshi and Shiqiang Wang},
    title     = {{Erasure Coded Neural Network Inference via Fisher Averaging}},
    booktitle = {International Symposium on Information Theory (ISIT)},
    year      = {2024},
    month     = {7},
    url       = {https://arxiv.org/abs/2409.01420}
  }

• On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data
  Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, and Tong Zhang
  Transactions of Machine Learning Research (TMLR), June 2024
  TMLR 2024arXiv

  BibTeX

  @article{wang2024on,
    author  = {Jianyu Wang and Rudrajit Das and Gauri Joshi and Satyen Kale and Zheng Xu and Tong Zhang},
    title   = {{On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data}},
    journal = {Transactions of Machine Learning Research (TMLR)},
    year    = {2024},
    month   = {6},
    url     = {http://arxiv.org/abs/2206.04723}
  }

• Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems
  Neharika Jali, Guannan Qu, Weina Wang, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024
  AISTATS 2024arXiv

  BibTeX

  @inproceedings{jali2024efficient,
    author    = {Neharika Jali and Guannan Qu and Weina Wang and Gauri Joshi},
    title     = {{Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2024},
    month     = {5},
    url       = {https://arxiv.org/abs/2402.01147}
  }

• FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
  Divyansh Jhunjhunwala, Shiqiang Wang, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024
  AISTATS 2024arXiv

  BibTeX

  @inproceedings{jhunjhunwala2024fedfisher,
    author    = {Divyansh Jhunjhunwala and Shiqiang Wang and Gauri Joshi},
    title     = {{FedFisher: Leveraging Fisher Information for One-Shot Federated Learning}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2024},
    month     = {5},
    url       = {https://arxiv.org/abs/2403.12329}
  }

• Maximizing Global Model Appeal in Federated Learning
  Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, and Gauri Joshi
  Transactions on Machine Learning Research (TMLR), Apr 2024
  TMLR 2024arXiv

  BibTeX

  @article{cho2024maximizing,
    author  = {Yae Jee Cho and Divyansh Jhunjhunwala and Tian Li and Virginia Smith and Gauri Joshi},
    title   = {{Maximizing Global Model Appeal in Federated Learning}},
    journal = {Transactions on Machine Learning Research (TMLR)},
    year    = {2024},
    month   = {4},
    url     = {https://arxiv.org/abs/2205.14840}
  }

• On Improved Distributed Random Reshuffling Over Networks
  Pranay Sharma, Jiarui Li, and Gauri Joshi
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), April 2024
  ICASSP 2024

  BibTeX

  @inproceedings{sharma2024on,
    author    = {Pranay Sharma and Jiarui Li and Gauri Joshi},
    title     = {{On Improved Distributed Random Reshuffling Over Networks}},
    booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
    year      = {2024},
    month     = {4},
    url       = {https://ieeexplore.ieee.org/abstract/document/10447202}
  }

2023

• Correlation aware Sparsified Mean Estimation Using Random Projection
  Shuli Jiang, Pranay Sharma, and Gauri Joshi
  Neural Information Processing Systems (NeurIPS), Dec 2023
  NeurIPS 2023arXiv

  BibTeX

  @inproceedings{jiang2023correlation,
    author    = {Shuli Jiang and Pranay Sharma and Gauri Joshi},
    title     = {{Correlation aware Sparsified Mean Estimation Using Random Projection}},
    booktitle = {Neural Information Processing Systems (NeurIPS)},
    year      = {2023},
    month     = {12},
    url       = {https://arxiv.org/abs/2310.18868}
  }

• Federated Minimax Optimization with Client Heterogeneity
  Pranay Sharma, Rohan Panda, and Gauri Joshi
  Transactions on Machine Learning Research (TMLR), Dec 2023
  TMLR 2023arXiv

  BibTeX

  @article{sharma2023federated,
    author  = {Pranay Sharma and Rohan Panda and Gauri Joshi},
    title   = {{Federated Minimax Optimization with Client Heterogeneity}},
    journal = {Transactions on Machine Learning Research (TMLR)},
    year    = {2023},
    month   = {12},
    url     = {https://arxiv.org/abs/2302.04249}
  }

• Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels
  Yae Jee Cho, Gauri Joshi, and Dimitrios Dimitriadis
  International Conference on Computer Vision (ICCV), Oct 2023
  ICCV 2023arXiv

  BibTeX

  @inproceedings{cho2023local,
    author    = {Yae Jee Cho and Gauri Joshi and Dimitrios Dimitriadis},
    title     = {{Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels}},
    booktitle = {International Conference on Computer Vision (ICCV)},
    year      = {2023},
    month     = {10},
    url       = {http://arxiv.org/abs/2307.08809}
  }

• Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information
  Divyansh Jhunjhunwala, Shiqiang Wang, and Gauri Joshi
  Federated Learning and Analytics workshop at ICML, July 2023
  paper

  BibTeX

  @inproceedings{jhunjhunwala2023towards,
    author    = {Divyansh Jhunjhunwala and Shiqiang Wang and Gauri Joshi},
    title     = {{Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information}},
    booktitle = {Federated Learning and Analytics workshop at ICML},
    year      = {2023},
    month     = {7},
    url       = {https://openreview.net/forum?id=YjvTJlcb8T}
  }

• The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond
  Jiin Woo, Gauri Joshi, and Yuejie Chi
  International Conference on Machine Learning (ICML), July 2023
  ICML 2023arXiv

  BibTeX

  @inproceedings{woo2023the,
    author    = {Jiin Woo and Gauri Joshi and Yuejie Chi},
    title     = {{The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2023},
    month     = {7},
    url       = {https://arxiv.org/abs/2305.10697}
  }

• On the Convergence of Federated Averaging with Cyclic Client Participation
  Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, and Tong Zhang
  International Conference on Machine Learning (ICML), July 2023
  ICML 2023arXiv

  BibTeX

  @inproceedings{cho2023on,
    author    = {Yae Jee Cho and Pranay Sharma and Gauri Joshi and Zheng Xu and Satyen Kale and Tong Zhang},
    title     = {{On the Convergence of Federated Averaging with Cyclic Client Participation}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2023},
    month     = {7},
    url       = {https://arxiv.org/abs/2302.03109}
  }

• FedExP: Speeding up Federated Averaging via Extrapolation
  Divyansh Jhunjhunwala, Shiqiang Wang, and Gauri Joshi
  International Conference on Learning Representations (ICLR), May 2023
  Selected for a Spotlight presentation (top 25% of accepted papers)
  ICLR 2023arXiv

  BibTeX

  @inproceedings{jhunjhunwala2023fedexp,
    author    = {Divyansh Jhunjhunwala and Shiqiang Wang and Gauri Joshi},
    title     = {{FedExP: Speeding up Federated Averaging via Extrapolation}},
    booktitle = {International Conference on Learning Representations (ICLR)},
    year      = {2023},
    month     = {5},
    url       = {https://arxiv.org/abs/2301.09604}
  }

• Federated Learning under Distributed Concept Drift
  Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, and Phillip B. Gibbons
  International Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2023
  Selected for an Oral presentation (top 6% of accepted papers)
  short version presented at the Workshop on Distribution Shifts at Neural Information Processing Systems, Dec 2022
  AISTATS 2023arXiv

  BibTeX

  @inproceedings{jothimurugesan2023federated,
    author    = {Ellango Jothimurugesan and Kevin Hsieh and Jianyu Wang and Gauri Joshi and Phillip B. Gibbons},
    title     = {{Federated Learning under Distributed Concept Drift}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2023},
    month     = {4},
    url       = {https://arxiv.org/abs/2206.00799}
  }

• Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer
  Yae Jee Cho, Jianyu Wang, Tarun Chiruvolu, and Gauri Joshi
  IEEE Journal of Selected Topics in Signal Processing, Jan 2023
  arXiv

  BibTeX

  @article{cho2023communicationefficient,
    author  = {Yae Jee Cho and Jianyu Wang and Tarun Chiruvolu and Gauri Joshi},
    title   = {{Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer}},
    journal = {IEEE Journal of Selected Topics in Signal Processing},
    year    = {2023},
    month   = {1},
    url     = {https://arxiv.org/abs/2109.08119}
  }

2022

• Optimization Algorithms for Distributed Machine Learning
  Gauri Joshi
  Spring Nature Synthesis Lectures on Learning, Networking and Algorithms, Dec 2022
  paper

  BibTeX

  @misc{joshi2022optimization,
    author       = {Gauri Joshi},
    title        = {{Optimization Algorithms for Distributed Machine Learning}},
    howpublished = {Spring Nature Synthesis Lectures on Learning, Networking and Algorithms},
    year         = {2022},
    month        = {12},
    url          = {https://link.springer.com/book/10.1007/978-3-031-19067-4}
  }

• To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning
  Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, and Gauri Joshi
  FedML Workshop at Neural Information Processing Systems, Dec 2022
  Selected for an oral presentation
  paper

  BibTeX

  @inproceedings{cho2022to,
    author    = {Yae Jee Cho and Divyansh Jhunjhunwala and Tian Li and Virginia Smith and Gauri Joshi},
    title     = {{To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning}},
    booktitle = {FedML Workshop at Neural Information Processing Systems},
    year      = {2022},
    month     = {12},
    url       = {https://openreview.net/forum?id=pG08eM0CQba}
  }

• Rateless Sum Recovery Codes for Distributed Non-linear Computations
  Ankur Mallick and Gauri Joshi
  Information Theory Workshop (ITW), Nov 2022
  ITW 2022

  BibTeX

  @inproceedings{mallick2022rateless,
    author    = {Ankur Mallick and Gauri Joshi},
    title     = {{Rateless Sum Recovery Codes for Distributed Non-linear Computations}},
    booktitle = {Information Theory Workshop (ITW)},
    year      = {2022},
    month     = {11},
    url       = {https://par.nsf.gov/servlets/purl/10389236}
  }

• Multi-Model Federated Learning with Provable Guarantees
  Neelkamal Bhuyan, Sharayu Moharir, and Gauri Joshi
  EAI Valuetools, Nov 2022
  arXiv

  BibTeX

  @misc{bhuyan2022multimodel,
    author       = {Neelkamal Bhuyan and Sharayu Moharir and Gauri Joshi},
    title        = {{Multi-Model Federated Learning with Provable Guarantees}},
    howpublished = {EAI Valuetools},
    year         = {2022},
    month        = {11},
    url          = {https://arxiv.org/abs/2207.04330}
  }

• MATCHA: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization
  Jianyu Wang, Anit Sahu, Gauri Joshi, and Soummya Kar
  IEEE Transactions on Signal Processing, Oct 2022
  Distinguished Student Paper Award for the earlier version at the NeurIPS Federated Learning workshop, 2019
  arXiv

  BibTeX

  @article{wang2022matcha,
    author  = {Jianyu Wang and Anit Sahu and Gauri Joshi and Soummya Kar},
    title   = {{MATCHA: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization}},
    journal = {IEEE Transactions on Signal Processing},
    year    = {2022},
    month   = {10},
    url     = {https://arxiv.org/abs/1905.09435}
  }

• Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers
  Tuhinangshu Choudhury, Weina Wang, and Gauri Joshi
  ACM MobiHoc, International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Oct 2022
  Best Paper Award
  arXiv

  BibTeX

  @inproceedings{choudhury2022tackling,
    author    = {Tuhinangshu Choudhury and Weina Wang and Gauri Joshi},
    title     = {{Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers}},
    booktitle = {ACM MobiHoc, International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing},
    year      = {2022},
    month     = {10},
    url       = {https://arxiv.org/abs/2207.03983}
  }

• Correlated Combinatorial Bandits for Online Resource Allocation
  Samarth Gupta, Jinhang Zuo, Carlee Joe-Wong, Gauri Joshi, and Osman Yagan
  ACM MobiHoc, International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Oct 2022
  Best Poster Award for a short version presented at SIGMETRICS 2022
  PDF

  BibTeX

  @inproceedings{gupta2022correlated,
    author    = {Samarth Gupta and Jinhang Zuo and Carlee Joe-Wong and Gauri Joshi and Osman Yagan},
    title     = {{Correlated Combinatorial Bandits for Online Resource Allocation}},
    booktitle = {ACM MobiHoc, International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing},
    year      = {2022},
    month     = {10}
  }

• FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning
  Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, and Gauri Joshi
  Conference on Uncertainty in Artificial Intelligence (UAI), Aug 2022
  UAI 2022arXiv

  BibTeX

  @inproceedings{jhunjhunwala2022fedvarp,
    author    = {Divyansh Jhunjhunwala and Pranay Sharma and Aushim Nagarkatti and Gauri Joshi},
    title     = {{FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning}},
    booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
    year      = {2022},
    month     = {8},
    url       = {https://arxiv.org/abs/2207.14130}
  }

• Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
  Sajad Khodadadian, Pranay Sharma, Gauri Joshi, and Siva Theja Maguluri
  International Conference on Machine Learning (ICML), July 2022
  selected for a long presentation (2.1% of submitted papers)
  ICML 2022arXiv

  BibTeX

  @inproceedings{khodadadian2022federated,
    author    = {Sajad Khodadadian and Pranay Sharma and Gauri Joshi and Siva Theja Maguluri},
    title     = {{Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2022},
    month     = {7},
    url       = {https://arxiv.org/abs/2206.10185}
  }

• Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
  Pranay Sharma, Rohan Panda, Gauri Joshi, and Pramod K. Varshney
  International Conference on Machine Learning (ICML), July 2022
  ICML 2022arXiv

  BibTeX

  @inproceedings{sharma2022federated,
    author    = {Pranay Sharma and Rohan Panda and Gauri Joshi and Pramod K. Varshney},
    title     = {{Federated Minimax Optimization: Improved Convergence Analyses and Algorithms}},
    booktitle = {International Conference on Machine Learning (ICML)},
    year      = {2022},
    month     = {7},
    url       = {https://arxiv.org/abs/2203.04850}
  }

• Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
  Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, and Dimitrios Dimitriadis
  International Joint Conference on Artificial Intelligence (IJCAI), July 2022
  IJCAI 2022arXiv

  BibTeX

  @inproceedings{cho2022heterogeneous,
    author    = {Yae Jee Cho and Andre Manoel and Gauri Joshi and Robert Sim and Dimitrios Dimitriadis},
    title     = {{Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning}},
    booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
    year      = {2022},
    month     = {7},
    url       = {https://arxiv.org/abs/2204.12703}
  }

• Chapter on Communication-Efficient Distributed Optimization Algorithms
  Shiqiang Wang and Gauri Joshi
  in the Book on "Federated Learning: A Comprehensive Overview of Methods and Applications", edited by Heiko Ludwig and Nathalie Baracaldo
  Springer Publications, July 2022
  paper

  BibTeX

  @incollection{wang2022chapter,
    author    = {Shiqiang Wang and Gauri Joshi},
    title     = {{Chapter on Communication-Efficient Distributed Optimization Algorithms}},
    booktitle = {in the Book on "Federated Learning: A Comprehensive Overview of Methods and Applications", edited by Heiko Ludwig and Nathalie Baracaldo},
    year      = {2022},
    url       = {https://www.barnesandnoble.com/w/federated-learning-heiko-ludwig/1140928320}
  }

• Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-vector Multiplication
  Ankur Mallick, Malhar Chaudhari, Ganesh Palanikumar, Utsav Sheth, and Gauri Joshi
  featured as a Research Highlight in the Communications of the ACM, May 2022
  paper

  BibTeX

  @article{mallick2022ratelessb,
    author  = {Ankur Mallick and Malhar Chaudhari and Ganesh Palanikumar and Utsav Sheth and Gauri Joshi},
    title   = {{Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-vector Multiplication}},
    journal = {\highlightfeatured as a Research Highlight in the Communications of the ACM},
    year    = {2022},
    month   = {5},
    url     = {https://dl.acm.org/doi/abs/10.1145/3524298}
  }

• Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems
  Ankur Mallick, Kevin Hsieh, Behnaz Arzani, and Gauri Joshi
  Conference on Machine Learning and Systems (MLSys), Aug 2022
  MLSys 2022

  BibTeX

  @inproceedings{mallick2022matchmaker,
    author    = {Ankur Mallick and Kevin Hsieh and Behnaz Arzani and Gauri Joshi},
    title     = {{Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems}},
    booktitle = {Conference on Machine Learning and Systems (MLSys)},
    year      = {2022},
    month     = {8},
    url       = {https://proceedings.mlsys.org/paper_files/paper/2022/hash/069a002768bcb31509d4901961f23b3c-Abstract.html}
  }

• A Dynamic Reweighting Strategy for Fair Federated Learning
  Zhiyuan Zhao and Gauri Joshi
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2022
  ICASSP 2022

  BibTeX

  @inproceedings{zhao2022a,
    author    = {Zhiyuan Zhao and Gauri Joshi},
    title     = {{A Dynamic Reweighting Strategy for Fair Federated Learning}},
    booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
    year      = {2022},
    month     = {5},
    url       = {https://ieeexplore.ieee.org/document/9746300}
  }

• Towards Understanding Biased Client Selection in Federated Learning
  Yae Jee Cho, Jianyu Wang, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), March 2022
  AISTATS 2022arXiv

  BibTeX

  @inproceedings{cho2022client,
    author    = {Yae Jee Cho and Jianyu Wang and Gauri Joshi},
    title     = {{Towards Understanding Biased Client Selection in Federated Learning}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2022},
    month     = {3},
    url       = {https://arxiv.org/abs/2010.01243}
  }

2021

• Local Adaptivity in Federated Learning: Convergence and Consistency
  Jianyu Wang, Zheng Xu, Zachary Garrett, Zachary Charles, Luyang Liu, and Gauri Joshi
  preprint, 2021
  arXiv

  BibTeX

  @misc{wang2021local,
    author       = {Jianyu Wang and Zheng Xu and Zachary Garrett and Zachary Charles and Luyang Liu and Gauri Joshi},
    title        = {{Local Adaptivity in Federated Learning: Convergence and Consistency}},
    howpublished = {preprint, 2021},
    year         = {2021},
    url          = {https://arxiv.org/abs/2106.02305}
  }

• FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients
  Jianyu Wang, Hang Qi, Ankit Singh Rawat, Sashank Reddi, Sagar Waghmare, Felix X. Yu, and Gauri Joshi
  preprint, 2021
  arXiv

  BibTeX

  @misc{wang2021fedlite,
    author       = {Jianyu Wang and Hang Qi and Ankit Singh Rawat and Sashank Reddi and Sagar Waghmare and Felix X. Yu and Gauri Joshi},
    title        = {{FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients}},
    howpublished = {preprint, 2021},
    year         = {2021},
    url          = {https://arxiv.org/abs/2201.11865}
  }

• Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation
  Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, and Gauri Joshi
  Neural Information Processing Systems (NeurIPS), Dec 2021
  NeurIPS 2021arXiv

  BibTeX

  @inproceedings{jhunjhunwala2021leveraging,
    author    = {Divyansh Jhunjhunwala and Ankur Mallick and Advait Gadhikar and Swanand Kadhe and Gauri Joshi},
    title     = {{Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation}},
    booktitle = {Neural Information Processing Systems (NeurIPS)},
    year      = {2021},
    month     = {12},
    url       = {https://arxiv.org/pdf/2110.07751.pdf}
  }

• Runtime estimation for machine learning tasks
  Parijat Dube, Gauri Joshi, Priya Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, and Zehra Noman Sura
  US Patent number 11200512, Dec 2021
  PDF

  BibTeX

  @misc{dube2021runtime,
    author       = {Parijat Dube and Gauri Joshi and Priya Nagpurkar and Stefania Costache and Diana Jeanne Arroyo and Zehra Noman Sura},
    title        = {{Runtime estimation for machine learning tasks}},
    howpublished = {US Patent number 11200512},
    year         = {2021},
    month        = {12},
    url          = {https://patentimages.storage.googleapis.com/c6/b7/38/c3ad6ba7feb9dc/US11200512.pdf}
  }

• Adaptive learning rate schedule in distributed stochastic gradient descent
  Parijat Dube, Sanghamitra Dutta, Gauri Joshi, and Priya Nagpurkar
  US Patent number 11182689, Nov 2021
  paper

  BibTeX

  @misc{dube2021adaptive,
    author       = {Parijat Dube and Sanghamitra Dutta and Gauri Joshi and Priya Nagpurkar},
    title        = {{Adaptive learning rate schedule in distributed stochastic gradient descent}},
    howpublished = {US Patent number 11182689},
    year         = {2021},
    month        = {11},
    url          = {https://patents.google.com/patent/US11182689B2/en}
  }

• Service Rate Region: A New Aspect of Coded Distributed System Design
  Mehmet Aktas, Gauri Joshi, Swanand Kadhe, Fatemeh Kazemi, and Emina Soljanin
  IEEE Transactions on Information Theory, Oct 2021
  arXiv

  BibTeX

  @article{aktas2021service,
    author  = {Mehmet Aktas and Gauri Joshi and Swanand Kadhe and Fatemeh Kazemi and Emina Soljanin},
    title   = {{Service Rate Region: A New Aspect of Coded Distributed System Design}},
    journal = {IEEE Transactions on Information Theory},
    year    = {2021},
    month   = {10},
    url     = {https://arxiv.org/pdf/2009.01598.pdf}
  }

• Rateless Codes for Distributed Non-linear Computations
  Ankur Mallick, Sophie Smith, and Gauri Joshi
  International Symposium on Topics in Coding, Sept 2021
  paper

  BibTeX

  @inproceedings{mallick2021rateless,
    author    = {Ankur Mallick and Sophie Smith and Gauri Joshi},
    title     = {{Rateless Codes for Distributed Non-linear Computations}},
    booktitle = {International Symposium on Topics in Coding},
    year      = {2021},
    month     = {9},
    url       = {https://ieeexplore.ieee.org/document/9594268}
  }

• Slow and Stale Gradients Can Win the Race
  Sanghamitra Dutta, Jianyu Wang, and Gauri Joshi
  Journal on Selected Areas of Information Theory (JSAIT) Special Issue, 2021
  JSAIT 2021arXiv

  BibTeX

  @article{dutta2021slow,
    author  = {Sanghamitra Dutta and Jianyu Wang and Gauri Joshi},
    title   = {{Slow and Stale Gradients Can Win the Race}},
    journal = {Journal on Selected Areas of Information Theory (JSAIT) Special Issue, 2021},
    year    = {2021},
    url     = {https://arxiv.org/abs/1803.01113}
  }

• A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning
  Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, and H. Vincent Poor
  IEEE Transactions on Signal Processing, Sept 2021
  paper

  BibTeX

  @article{wang2021a,
    author  = {Jianyu Wang and Qinghua Liu and Hao Liang and Gauri Joshi and H. Vincent Poor},
    title   = {{A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning}},
    journal = {IEEE Transactions on Signal Processing},
    year    = {2021},
    month   = {9},
    url     = {https://ieeexplore.ieee.org/document/9521822}
  }

• A Field Guide to Federated Optimization
  53 authors including primary editors Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi and H. Brendan McMahan
  Technical Report, July 2021
  arXiv

  BibTeX

  @misc{joshi2021a,
    title        = {{A Field Guide to Federated Optimization}},
    howpublished = {Technical Report},
    year         = {2021},
    month        = {7},
    url          = {https://arxiv.org/abs/2107.06917}
  }

• Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning
  Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, and Yonina C. Eldar
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021
  ICASSP 2021arXiv

  BibTeX

  @inproceedings{jhunjhunwala2021adaptive,
    author    = {Divyansh Jhunjhunwala and Advait Gadhikar and Gauri Joshi and Yonina C. Eldar},
    title     = {{Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning}},
    booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
    year      = {2021},
    month     = {6},
    url       = {https://arxiv.org/abs/2102.04487}
  }

• Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms
  Jianyu Wang and Gauri Joshi
  Journal of Machine Learning Research (JMLR), 2021
  JMLR 2021arXiv

  BibTeX

  @article{wang2021cooperative,
    author  = {Jianyu Wang and Gauri Joshi},
    title   = {{Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms}},
    journal = {Journal of Machine Learning Research (JMLR), 2021},
    year    = {2021},
    url     = {https://arxiv.org/abs/1808.07576}
  }

• Advances and Open Problems in Federated Learning
  58 authors, including Peter Kairouz, Brendan McMahan, Jianyu Wang and Gauri Joshi
  Foundations and Trends in Machine Learning, 2021
  arXiv

  BibTeX

  @misc{joshi2021advances,
    title        = {{Advances and Open Problems in Federated Learning}},
    howpublished = {Foundations and Trends in Machine Learning, 2021},
    year         = {2021},
    url          = {https://arxiv.org/abs/1912.04977}
  }

• Machine Learning on Volatile Instances
  Xiaoxi Zhang, Jianyu Wang, Li-Feng Lee, Tom Yang, Akansha Kalra, Gauri Joshi, and Carlee Joe-Wong
  IEEE/ACM Transactions on Networking, Sept 2021
  arXiv

  BibTeX

  @article{zhang2021machine,
    author  = {Xiaoxi Zhang and Jianyu Wang and Li-Feng Lee and Tom Yang and Akansha Kalra and Gauri Joshi and Carlee Joe-Wong},
    title   = {{Machine Learning on Volatile Instances}},
    journal = {IEEE/ACM Transactions on Networking},
    year    = {2021},
    month   = {9},
    url     = {https://arxiv.org/abs/2003.05649}
  }

• Synergy via Redundancy: Adaptive Replication Strategies and Fundamental Limits
  Gauri Joshi and Dhruva Kaushal
  IEEE ACM/Transactions on Networking, 2021
  PDF

  BibTeX

  @article{joshi2021synergy,
    author  = {Gauri Joshi and Dhruva Kaushal},
    title   = {{Synergy via Redundancy: Adaptive Replication Strategies and Fundamental Limits}},
    journal = {IEEE ACM/Transactions on Networking, 2021},
    year    = {2021}
  }

• Job Dispatching Policies for Queueing Systems with Unknown Service Rates
  Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, and Sanjay Shakkottai
  ACM MobiHoc, July 2021
  arXiv

  BibTeX

  @inproceedings{choudhury2021job,
    author    = {Tuhinangshu Choudhury and Gauri Joshi and Weina Wang and Sanjay Shakkottai},
    title     = {{Job Dispatching Policies for Queueing Systems with Unknown Service Rates}},
    booktitle = {ACM MobiHoc},
    year      = {2021},
    month     = {7},
    url       = {https://arxiv.org/abs/2106.04707}
  }

• Best-arm Identification in Correlated Multi-armed Bandits
  Samarth Gupta, Gauri Joshi, and Osman Yagan
  Journal on Selected Areas of Information Theory (JSAIT) Special Issue on Sequential, Active, and Reinforcement Learning, 2021
  JSAIT 2021PDF

  BibTeX

  @article{gupta2021bestarm,
    author  = {Samarth Gupta and Gauri Joshi and Osman Yagan},
    title   = {{Best-arm Identification in Correlated Multi-armed Bandits}},
    journal = {Journal on Selected Areas of Information Theory (JSAIT) Special Issue on Sequential, Active, and Reinforcement Learning, 2021},
    year    = {2021},
    url     = {https://ieeexplore.ieee.org/document/9437336}
  }

• Multi-armed Bandits with Correlated Arms
  Samarth Gupta, Shreyas Chaudhari, Gauri Joshi, and Osman Yagan
  IEEE Transactions on Information Theory, May 2021
  shorter version appeared in the ICML Workshop on Theoretical Foundations of RL, July 2020
  arXiv

  BibTeX

  @article{gupta2021multiarmed,
    author  = {Samarth Gupta and Shreyas Chaudhari and Gauri Joshi and Osman Yagan},
    title   = {{Multi-armed Bandits with Correlated Arms}},
    journal = {IEEE Transactions on Information Theory},
    year    = {2021},
    month   = {5},
    url     = {https://arxiv.org/abs/1911.03959}
  }

• A Unified Approach to Translate Classic Bandit Algorithms to the Structured Bandit Setting
  Samarth Gupta, Shreyas Chaudhari, Subhojyoti Mukherjee, Gauri Joshi, and Osman Yagan
  Journal on Selected Areas of Information Theory (JSAIT) Special Issue on Estimation and Inference, 2021
  shorter version in International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021
  JSAIT 2021arXiv

  BibTeX

  @article{gupta2021a,
    author  = {Samarth Gupta and Shreyas Chaudhari and Subhojyoti Mukherjee and Gauri Joshi and Osman Yagan},
    title   = {{A Unified Approach to Translate Classic Bandit Algorithms to the Structured Bandit Setting}},
    journal = {Journal on Selected Areas of Information Theory (JSAIT) Special Issue on Estimation and Inference, 2021},
    year    = {2021},
    url     = {https://arxiv.org/pdf/1810.08164.pdf}
  }

• Deep Kernels with Probabilistic Embeddings for Small-Data Learning
  Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, and T. Yong-Jin Han
  Conference on Uncertainty in Artificial Intelligence (UAI), July 2021
  Selected for an Oral Presentation
  shorter version in the ICLR From Shallow to Deep: Overcoming Limited and Adverse Data (S2D-OLAD) Workshop, May 2021
  UAI 2021arXiv

  BibTeX

  @inproceedings{mallick2021deep,
    author    = {Ankur Mallick and Chaitanya Dwivedi and Bhavya Kailkhura and Gauri Joshi and T. Yong-Jin Han},
    title     = {{Deep Kernels with Probabilistic Embeddings for Small-Data Learning}},
    booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
    year      = {2021},
    month     = {7},
    url       = {https://arxiv.org/abs/1910.05858}
  }

2020

• Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
  Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, and H. Vincent Poor
  Neural Information Processing Systems (NeurIPS), Dec 2020
  Best Poster Award at the NSF TRIPODS workshop on communication-efficient distributed optimization
  NeurIPS 2020arXiv

  BibTeX

  @inproceedings{wang2020tackling,
    author    = {Jianyu Wang and Qinghua Liu and Hao Liang and Gauri Joshi and H. Vincent Poor},
    title     = {{Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization}},
    booktitle = {Neural Information Processing Systems (NeurIPS)},
    year      = {2020},
    month     = {12},
    url       = {https://arxiv.org/abs/2007.07481}
  }

• Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning
  Yae Jee Cho, Samarth Gupta, Gauri Joshi, and Osman Yagan
  Asilomar Conference, Nov 2020
  arXiv

  BibTeX

  @inproceedings{cho2020banditbased,
    author    = {Yae Jee Cho and Samarth Gupta and Gauri Joshi and Osman Yagan},
    title     = {{Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning}},
    booktitle = {Asilomar Conference},
    year      = {2020},
    month     = {11},
    url       = {http://arxiv.org/abs/2012.08009}
  }

• Exploring the Error-Runtime Trade-off in Decentralized Optimization
  Jianyu Wang, Anit Sahu, Gauri Joshi, and Soummya Kar
  Asilomar Conference, Nov 2020
  PDF

  BibTeX

  @inproceedings{wang2020exploring,
    author    = {Jianyu Wang and Anit Sahu and Gauri Joshi and Soummya Kar},
    title     = {{Exploring the Error-Runtime Trade-off in Decentralized Optimization}},
    booktitle = {Asilomar Conference},
    year      = {2020},
    month     = {11}
  }

• Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-vector Multiplication
  Ankur Mallick, Malhar Chaudhari, Ganesh Palanikumar, Utsav Sheth, and Gauri Joshi
  ACM SIGMETRICS, June 2020
  Best Paper Award
  arXiv

  BibTeX

  @inproceedings{mallick2020rateless,
    author    = {Ankur Mallick and Malhar Chaudhari and Ganesh Palanikumar and Utsav Sheth and Gauri Joshi},
    title     = {{Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-vector Multiplication}},
    booktitle = {ACM SIGMETRICS},
    year      = {2020},
    month     = {6},
    url       = {https://arxiv.org/abs/1804.10331}
  }

• Correlated Multi-armed Bandits with a Latent Random Source
  Samarth Gupta, Gauri Joshi, and Osman Yagan
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2020
  ICASSP 2020arXiv

  BibTeX

  @inproceedings{gupta2020correlated,
    author    = {Samarth Gupta and Gauri Joshi and Osman Yagan},
    title     = {{Correlated Multi-armed Bandits with a Latent Random Source}},
    booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
    year      = {2020},
    month     = {5},
    url       = {https://arxiv.org/abs/1808.05904}
  }

• Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD
  Jianyu Wang, Hao Liang, and Gauri Joshi
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2020
  ICASSP 2020PDF

  BibTeX

  @inproceedings{wang2020overlap,
    author    = {Jianyu Wang and Hao Liang and Gauri Joshi},
    title     = {{Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD}},
    booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
    year      = {2020},
    month     = {5},
    url       = {https://ieeexplore.ieee.org/document/9053834}
  }

• Machine Learning on Volatile Instances
  Xiaoxi Zhang, Jianyu Wang, Gauri Joshi, and Carlee Joe-Wong
  IEEE Intl. Conf. on Computer Communications (INFOCOM), April 2020
  INFOCOM 2020PDF

  BibTeX

  @inproceedings{zhang2020machine,
    author    = {Xiaoxi Zhang and Jianyu Wang and Gauri Joshi and Carlee Joe-Wong},
    title     = {{Machine Learning on Volatile Instances}},
    booktitle = {IEEE Intl. Conf. on Computer Communications (INFOCOM)},
    year      = {2020},
    month     = {4},
    url       = {https://dl.acm.org/doi/10.1109/INFOCOM41043.2020.9155448}
  }

• Accelerating Deep Learning by Focusing on the Biggest Losers
  Angela H. Jiang, Daniel L.-K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminksy, Michael Kozuch, Zachary C. Lipton, and Padmanabhan Pillai
  preprint
  arXiv

  BibTeX

  @misc{jiang2020accelerating,
    author = {Angela H. Jiang and Daniel L.-K. Wong and Giulio Zhou and David G. Andersen and Jeffrey Dean and Gregory R. Ganger and Gauri Joshi and Michael Kaminksy and Michael Kozuch and Zachary C. Lipton and Padmanabhan Pillai},
    title  = {{Accelerating Deep Learning by Focusing on the Biggest Losers}},
    year   = {2020},
    url    = {https://arxiv.org/abs/1910.00762}
  }

2019

• Rateless Codes for Distributed Computations with Sparse Compressed Matrices
  Ankur Mallick and Gauri Joshi
  international Symposium on Information Theory (ISIT), July 2019
  ISIT 2019PDF

  BibTeX

  @inproceedings{mallick2019rateless,
    author    = {Ankur Mallick and Gauri Joshi},
    title     = {{Rateless Codes for Distributed Computations with Sparse Compressed Matrices}},
    booktitle = {international Symposium on Information Theory (ISIT)},
    year      = {2019},
    month     = {7},
    url       = {https://ieeexplore.ieee.org/document/8849306}
  }

• Fast and Efficient Distributed Matrix-Vector Multiplication Using Rateless Fountain Codes
  Ankur Mallick, Malhar Chaudhari, and Gauri Joshi
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2019
  ICASSP 2019PDF

  BibTeX

  @inproceedings{mallick2019fast,
    author    = {Ankur Mallick and Malhar Chaudhari and Gauri Joshi},
    title     = {{Fast and Efficient Distributed Matrix-Vector Multiplication Using Rateless Fountain Codes}},
    booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2019},
    year      = {2019},
    url       = {https://ieeexplore.ieee.org/document/8682347}
  }

• Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
  Jianyu Wang and Gauri Joshi
  SysML Conference, March 2019
  arXiv

  BibTeX

  @inproceedings{wang2019adaptive,
    author    = {Jianyu Wang and Gauri Joshi},
    title     = {{Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD}},
    booktitle = {SysML Conference},
    year      = {2019},
    month     = {3},
    url       = {https://arxiv.org/abs/1810.08313}
  }

• Efficient Straggler Replication in Large-scale Parallel Computing
  Da Wang, Gauri Joshi, and Gregory Wornell
  ACM Trans. on Modeling and Perf. Eval. of Comp. Systems, 2019
  arXiv

  BibTeX

  @misc{wang2019efficient,
    author       = {Da Wang and Gauri Joshi and Gregory Wornell},
    title        = {{Efficient Straggler Replication in Large-scale Parallel Computing}},
    howpublished = {ACM Trans. on Modeling and Perf. Eval. of Comp. Systems, 2019},
    year         = {2019},
    url          = {http://arxiv.org/abs/1503.03128}
  }

2018

• Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
  Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, and Priya Nagpurkar
  International Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2018
  AISTATS 2018arXiv

  BibTeX

  @inproceedings{dutta2018slow,
    author    = {Sanghamitra Dutta and Gauri Joshi and Soumyadip Ghosh and Parijat Dube and Priya Nagpurkar},
    title     = {{Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD}},
    booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    year      = {2018},
    month     = {4},
    url       = {https://arxiv.org/abs/1803.01113}
  }

• Active Distribution Learning from Indirect Samples
  Samarth Gupta, Gauri Joshi, and Osman Yagan
  Allerton Conference on Communication, Control and Computing, Oct 2018
  arXiv

  BibTeX

  @inproceedings{gupta2018active,
    author    = {Samarth Gupta and Gauri Joshi and Osman Yagan},
    title     = {{Active Distribution Learning from Indirect Samples}},
    booktitle = {Allerton Conference on Communication, Control and Computing},
    year      = {2018},
    month     = {10},
    url       = {https://arxiv.org/abs/1808.05334}
  }

• Service Capacity Region of Content Access from Erasure Coded Storage
  Sarah E. Anderson, Ann Johnston, Gauri Joshi, Gretchen L. Matthews, Carolyn Mayer, and Emina Soljanin
  IEEE Information Theory Workshop, Nov 2018
  PDF

  BibTeX

  @inproceedings{anderson2018service,
    author    = {Sarah E. Anderson and Ann Johnston and Gauri Joshi and Gretchen L. Matthews and Carolyn Mayer and Emina Soljanin},
    title     = {{Service Capacity Region of Content Access from Erasure Coded Storage}},
    booktitle = {IEEE Information Theory Workshop},
    year      = {2018},
    month     = {11}
  }

2017

• Synergy via Redundancy: Boosting Service Capacity via Adaptive Task Replication
  Gauri Joshi
  ACM/IFIP Performance, Nov 2017
  PDF

  BibTeX

  @misc{joshi2017synergy,
    author       = {Gauri Joshi},
    title        = {{Synergy via Redundancy: Boosting Service Capacity via Adaptive Task Replication}},
    howpublished = {ACM/IFIP Performance},
    year         = {2017},
    month        = {11}
  }

• On the Service Capacity Region of Accessing Erasure Coded Content
  Mehmet Aktas, Sarah E. Anderson, Ann Johnston, Gauri Joshi, Swanand Kadhe, Gretchen L. Matthews, Carolyn Mayer, and Emina Soljanin
  Allerton Conference on Communication, Control, and Computing, Oct 2017
  PDF

  BibTeX

  @inproceedings{aktas2017on,
    author    = {Mehmet Aktas and Sarah E. Anderson and Ann Johnston and Gauri Joshi and Swanand Kadhe and Gretchen L. Matthews and Carolyn Mayer and Emina Soljanin},
    title     = {{On the Service Capacity Region of Accessing Erasure Coded Content}},
    booktitle = {Allerton Conference on Communication, Control, and Computing},
    year      = {2017},
    month     = {10}
  }

• Efficient Redundancy Techniques for Latency Reduction in Cloud Systems
  Gauri Joshi, Emina Soljanin, and Gregory Wornell
  ACM Trans. on Modeling and Perf. Eval. of Comp. Systems, vol. 2, no. 12, May 2017
  PDF

  BibTeX

  @misc{joshi2017efficient,
    author       = {Gauri Joshi and Emina Soljanin and Gregory Wornell},
    title        = {{Efficient Redundancy Techniques for Latency Reduction in Cloud Systems}},
    howpublished = {ACM Trans. on Modeling and Perf. Eval. of Comp. Systems, vol. 2, no. 12},
    year         = {2017},
    month        = {5}
  }

• Boosting Service Capacity via Adaptive Task Replication
  Gauri Joshi
  ACM Sigmetrics MAMA workshop, Jun 2017
  PDF

  BibTeX

  @inproceedings{joshi2017boosting,
    author    = {Gauri Joshi},
    title     = {{Boosting Service Capacity via Adaptive Task Replication}},
    booktitle = {ACM Sigmetrics MAMA workshop},
    year      = {2017},
    month     = {6}
  }

2015-2016

• Efficient Redundancy Techniques to Reduce Delay in Cloud Systems
  Doctoral Thesis, MIT, June 2016
  PDF

  BibTeX

  @phdthesis{joshi2016efficient,
    author = {Gauri Joshi},
    title  = {{Efficient Redundancy Techniques to Reduce Delay in Cloud Systems}},
    school = {Doctoral Thesis, MIT},
    year   = {2016},
    month  = {6}
  }

• Efficient Replication of Queued Tasks to Reduce Latency in Cloud Systems
  Gauri Joshi, Emina Soljanin, and Gregory Wornell
  Allerton Conference on Communication, Control and Computing, Oct 2015
  PDF

  BibTeX

  @inproceedings{joshi2015efficient,
    author    = {Gauri Joshi and Emina Soljanin and Gregory Wornell},
    title     = {{Efficient Replication of Queued Tasks to Reduce Latency in Cloud Systems}},
    booktitle = {Allerton Conference on Communication, Control and Computing},
    year      = {2015},
    month     = {10}
  }

• Queues with Redundancy: Latency-Cost Analysis
  Gauri Joshi, Emina Soljanin, and Gregory Wornell
  Mathematical Modeling and Analysis (MAMA) Workshop, Jun 2015
  PDF

  BibTeX

  @inproceedings{joshi2015queues,
    author    = {Gauri Joshi and Emina Soljanin and Gregory Wornell},
    title     = {{Queues with Redundancy: Latency-Cost Analysis}},
    booktitle = {Mathematical Modeling and Analysis (MAMA) Workshop},
    year      = {2015},
    month     = {6}
  }

• Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing
  Da Wang, Gauri Joshi, and Gregory Wornell
  Distributed Cloud Computing (DCC) Workshop, Jun 2015
  PDF

  BibTeX

  @inproceedings{wang2015using,
    author    = {Da Wang and Gauri Joshi and Gregory Wornell},
    title     = {{Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing}},
    booktitle = {Distributed Cloud Computing (DCC) Workshop},
    year      = {2015},
    month     = {6}
  }

• Playback Delay in On-Demand Streaming Communication with Feedback
  Kaveh Mahadaviani, Ashish Khisti, Gauri Joshi, and Gregory Wornell
  International Symposium on Information Theory, July 2015
  PDF

  BibTeX

  @inproceedings{mahadaviani2015playback,
    author    = {Kaveh Mahadaviani and Ashish Khisti and Gauri Joshi and Gregory Wornell},
    title     = {{Playback Delay in On-Demand Streaming Communication with Feedback}},
    booktitle = {International Symposium on Information Theory},
    year      = {2015},
    month     = {7}
  }

2014

• Efficient Job Replication for Fast Response Times in Parallel Computation
  Da Wang, Gauri Joshi, and Gregory Wornell
  ACM Sigmetrics short paper Jun 2014
  PDF

  BibTeX

  @inproceedings{wang2014efficient,
    author    = {Da Wang and Gauri Joshi and Gregory Wornell},
    title     = {{Efficient Job Replication for Fast Response Times in Parallel Computation}},
    booktitle = {ACM Sigmetrics short paper},
    year      = {2014},
    month     = {6}
  }

• Throughput-Smoothness Trade-offs in Multicasting an Ordered Packet Stream
  Gauri Joshi, Yuval Kochman, and Gregory Wornell
  International Symposium on Network Coding, Jun 2014
  PDF

  BibTeX

  @inproceedings{joshi2014throughputsmoothness,
    author    = {Gauri Joshi and Yuval Kochman and Gregory Wornell},
    title     = {{Throughput-Smoothness Trade-offs in Multicasting an Ordered Packet Stream}},
    booktitle = {International Symposium on Network Coding},
    year      = {2014},
    month     = {6}
  }

• On the Delay-Storage Trade-off in Content Download from Distributed Storage
  Gauri Joshi, Yanpei Liu, and Emina Soljanin
  IEEE Journal on Selected Areas of Communications, vol. 32, no. 5, May 2014
  PDF

  BibTeX

  @article{joshi2014on,
    author  = {Gauri Joshi and Yanpei Liu and Emina Soljanin},
    title   = {{On the Delay-Storage Trade-off in Content Download from Distributed Storage}},
    journal = {IEEE Journal on Selected Areas of Communications, vol. 32, no. 5},
    year    = {2014},
    month   = {5}
  }

• Effect of Block-wise Feedback on the Throughput-Delay Trade-off in Streaming
  Gauri Joshi, Yuval Kochman, and Gregory Wornell
  INFOCOM workshop on Contemporary Video, Apr 2014
  PDF

  BibTeX

  @inproceedings{joshi2014effect,
    author    = {Gauri Joshi and Yuval Kochman and Gregory Wornell},
    title     = {{Effect of Block-wise Feedback on the Throughput-Delay Trade-off in Streaming}},
    booktitle = {INFOCOM workshop on Contemporary Video},
    year      = {2014},
    month     = {4}
  }

2012-2013

• Round-robin Overlapping Generations Coding for Fast Content Download
  Gauri Joshi and Emina Soljanin
  International Symposium on Information Theory, Jul 2013
  PDF

  BibTeX

  @inproceedings{joshi2013roundrobin,
    author    = {Gauri Joshi and Emina Soljanin},
    title     = {{Round-robin Overlapping Generations Coding for Fast Content Download}},
    booktitle = {International Symposium on Information Theory},
    year      = {2013},
    month     = {7}
  }

• Coding for Fast Content Download
  Gauri Joshi, Yanpei Liu, and Emina Soljanin
  Allerton Conference on Communication, Control and Computing, Oct 2012
  PDF

  BibTeX

  @inproceedings{joshi2012coding,
    author    = {Gauri Joshi and Yanpei Liu and Emina Soljanin},
    title     = {{Coding for Fast Content Download}},
    booktitle = {Allerton Conference on Communication, Control and Computing},
    year      = {2012},
    month     = {10}
  }

• On Playback Delay in Streaming Communication
  Gauri Joshi, Yuval Kochman, and Gregory Wornell
  International Symposium on Information Theory, Jul 2012
  PDF

  BibTeX

  @inproceedings{joshi2012on,
    author    = {Gauri Joshi and Yuval Kochman and Gregory Wornell},
    title     = {{On Playback Delay in Streaming Communication}},
    booktitle = {International Symposium on Information Theory},
    year      = {2012},
    month     = {7}
  }

• On Playback Delay in Streaming Communication
  Masters Thesis, MIT, May 2012
  William Martin Memorial Best Thesis Award
  PDF

  BibTeX

  @mastersthesis{joshi2012onb,
    author = {Gauri Joshi},
    title  = {{On Playback Delay in Streaming Communication}},
    school = {Masters Thesis, MIT},
    year   = {2012},
    month  = {5}
  }

2010-2011

• Fountain Codes
  Gauri Joshi, Joong Bum Rhim, John Sun, and Da Wang
  Project Report 6.451, Dec 2010
  PDF

  BibTeX

  @misc{joshi2010fountain,
    author       = {Gauri Joshi and Joong Bum Rhim and John Sun and Da Wang},
    title        = {{Fountain Codes}},
    howpublished = {Project Report 6.451},
    year         = {2010},
    month        = {12}
  }

• Downlink Erlang Capacity of Cellular OFDMA
  Gauri Joshi, Harshad Maral, and Abhay Karandikar
  National Conference on Communications, Jan 2011
  PDF

  BibTeX

  @inproceedings{joshi2011downlink,
    author    = {Gauri Joshi and Harshad Maral and Abhay Karandikar},
    title     = {{Downlink Erlang Capacity of Cellular OFDMA}},
    booktitle = {National Conference on Communications},
    year      = {2011},
    month     = {1}
  }

• Optimal Relay Placement for Cellular Coverage Extension
  Gauri Joshi and Abhay Karandikar
  National Conference on Communications, Jan 2011
  PDF

  BibTeX

  @inproceedings{joshi2011optimal,
    author    = {Gauri Joshi and Abhay Karandikar},
    title     = {{Optimal Relay Placement for Cellular Coverage Extension}},
    booktitle = {National Conference on Communications},
    year      = {2011},
    month     = {1}
  }

• Performance Analysis of Active Handoff in CDMA2000 Femtocells
  Gauri Joshi, Mehmet Yavuz, and Chirag Patel
  National Conference on Communications, Jan 2010
  PDF

  BibTeX

  @inproceedings{joshi2010performance,
    author    = {Gauri Joshi and Mehmet Yavuz and Chirag Patel},
    title     = {{Performance Analysis of Active Handoff in CDMA2000 Femtocells}},
    booktitle = {National Conference on Communications},
    year      = {2010},
    month     = {1}
  }

• On Relay-assisted Cellular Networks
  Masters Thesis, IIT Bombay, June 2010
  PDF

  BibTeX

  @mastersthesis{joshi2010on,
    author = {Gauri Joshi},
    title  = {{On Relay-assisted Cellular Networks}},
    school = {Masters Thesis, IIT Bombay},
    year   = {2010},
    month  = {6}
  }