Publications by Topic
Notice: A paper below may not be the most recent version. Send me an e-mail if you are interested in an up to date copy. The copyright of the published papers below have been transferred to the respective publishers.
Topics:
Foundations of Machine Learning
Resource Allocation
Energy Efficient Computing
Web Advertising
Foundations of Machine Learning :
-
Polynomial Time Convergence of the Iterative Evaluation of Datalogo Programs
with: Sungjin Im, Hung Ngo and Kirk Pruhs
Symposium on Principles of Database Systems (PODS 2025)
- Binary Search Tree with Distributional Predictions
with: Michael Dinitz, Sungjin Im, Thomas Lavastida, Aidin Niaparast, and Sergei Vassilvitskii
Neural Information Processing Systems (NeurIPS 2024)
-
Online k-Median with Consistent Clusters
with: Heather Newman and Kirk Pruhs
International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2024)
-
Incremental Topological Ordering and Cycle Detection with Predictions
with: Samuel McCauley Aidin Niaparast, and Shikha Singh
International Conference on Machine Learning (ICML 2024)
-
Simultaneously Approximating All lp-norms in Correlation Clustering
with: Sami Davies, and Heather Newman
International Colloquium on Automata, Languages, and Programming (ICALP 2024)
-
Sampling for Beyond-Worst-Case Online Ranking
with: Qingyun Chen, Sungjin Im, Chenyang Xu, and Ruilong Zhang
AAAI Confernce on Artificial Intelligence (AAAI 2024)
-
On the Convergence Rate of Linear Datalogoover Stable Semirings
with: Sungjin Im, Hung Ngo, and Kirk Pruhs
International Conference on Database Theory (ICDT 2024)
-
Massively Parallel Computation: Algorithms and Applications
with: Sungjin Im, Ravi Kumar, Silvio Lattanzi, and Sergei Vassilvitskii
Foundations and Trends in Optimization (FnT)
Book/Tutorial on Massively Parallel Algorithms
-
Online List Labeling with Predictions
with: Samuel McCauley Aidin Niaparast, and Shikha Singh
Neural Information Processing Systems (NeurIPS 2023)
Spotlight Presentation.
-
Fast Combinatorial Algorithms for Min Max Correlation Clustering
with: Sami Davies and Heather Newman
International Conference on Machine Learning(ICML 2023)
-
Predictive Flows for Faster Ford-Fulkerson
with: Sami Davies, Sergei Vassilvitskii, and Yuyan Wang
International Conference on Machine Learning(ICML 2023)
-
Online Dynamic Acknowledgement with Learned Predictions
with: Sungjin Im, Chenyang Xu, and Ruilong Zhang
IEEE International Conference on Computer Communications (INFOCOM 2023)
-
Min-Max Submodular Ranking for Multiple Agents
with: Qingyun Chen, Sungjin Im, Chenyang Xu, and Ruilong Zhang
AAAI Confernce on Artificial Intelligence (AAAI 2023)
-
Online State Exploration: Competitive Worst Case and Learning-Augmented Algorithms
with: Sungjin Im, Chenyang Xu, and Ruilong Zhang
European Conference on Machine Learning (ECML 2023)
-
Algorithms with Prediction Portfolios
with: Michael Dinitz, Sungjin Im, Thomas Lavastida, and Sergei Vassilvitskii
Neural Information Processing Systems (NeurIPS 2022)
-
Learning-Augmented Algorithms for Online Steiner Tree
with: Chenyang Xu
AAAI Confernce on Artificial Intelligence (AAAI 2022)
-
Faster Matchings via Learned Duals
with: Michael Dinitz, Sungjin Im, Thomas Lavastida, and Sergei Vassilvitskii
Neural Information Processing Systems (NeurIPS 2021)
Oral Presentation. Orals had a less than 1% acceptence rate.
-
Robust Online Correlation Clustering
with: Silvio Lattanzi, Sergei Vassilvitskii, Yuyan Wang, and Rudy Zhou
Neural Information Processing Systems (NeurIPS 2021)
-
Structural Iterative Rounding for Generalized k-Median Problems
with: Anupam Gupta and Rudy Zhou
International Colloquium on Automata, Languages, and Programming (ICALP 2021)
-
Relational Algorithms for k-means Clustering
with: Kirk Pruhs, Alireza Samadian and Yuyan Wang
International Colloquium on Automata, Languages, and Programming (ICALP 2021)
-
Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors
with: Sergei Vassilvitskii and Yuyan Wang
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2021)
-
Learnable and Instance-Robust Predictions for Online Matching, Flows and Load Balancing
with: Thomas Lavastida, R. Ravi and Chenyang Xu
European Symposium on Algorithms (ESA 2021)
-
Scaling Average-Linkage via Sparse Cluster Embeddings
with: Kefu Lu, Thomas Lavastida, and Yuyan Wang
Asian Conference on Machine Learning (ACML 2021)
-
An Approximation Algorithm for the Matrix Tree Multiplication Problem
with: Mahmoud Abo Khamis, Ryan Curtin, Sungjin Im, Hung Ngo, Kirk Pruhs and Alireza Samadian
Mathematical Foundations of Computer Science (MFCS 2021)
-
Using Predicted Weights for Ad Delivery
with: Thomas Lavastida, R. Ravi and Chenyang Xu
SIAM Conference on Applied and Computational Discrete Algorithms (ACDA 2021)
-
A Scalable Approximation Algorithm for Weighted Longest Common Subsequence
with: Jeremy Buhler, Thomas Lavastida, and Kefu Lu
In Proceedings of the International European Conference on Parallel and Distributed Computing (Euro-Par 2021)
-
Instance Optimal Join Size Estimation
with: Mahmoud Abo-Khamis, Sungjin Im, Kirk Pruhs, and Alireza Samadian
Latin and American Algorithms, Graphs and Optimization Symposium (LAGOS 2021)
-
Approximate Aggregate Queries Under Additive Inequalities
with: Mahmoud Abo-Khamis, Sungjin Im, Kirk Pruhs, and Alireza Samadian
SIAM-ACM Symposium on Algorithmic Principles of Computer Systems (APoCS 2021)
-
A Relational Gradient Descent Algorithm For Support Vector Machine Training
with: Mahmoud Abo-Khamis, Sungjin Im, Kirk Pruhs, and Alireza Samadian
SIAM-ACM Symposium on Algorithmic Principles of Computer Systems (APoCS 2021)
-
Fair Hierarchical Clustering
with: Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Philip Pham, Sergei Vassilvitskii and Yuyan Wang
Neural Information Processing System (NeurIPS 2020)
- Fast Noise Removal for k-means Clustering
with: Sungjin Im, Mashid Qaem, Xiaorui Sun, and Rudy Zhou
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
- Unconditional Coresets for Regularized Loss Minimization
with: Alireza Samadian, Kirk Pruhs, Sungjin Im, and Ryan Curtain
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
- Rk-means: Fast Clustering for Relational Data
with:Ryan Curtain, Hung Ngo, XuanLong Nguyen, Dan Olteanu, Maximillian Schleich
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
-
An Objective for Hierarchical Clustering in Euclidean Space and its Connection to Bisecting K-means
with: Yuyan Wang
AAAI Conference on Artificial Intelligence (AAAI 2020)
-
Online Scheduling via Learned Weights
with: Silvio Lattanzi, Thomas Lavastida, and Sergei Vassilvitskii
ACM-SIAM Symposium on Discrete Algorithms (SODA 2020)
-
Cost Effective Active Search
with: Shali Jiang and Roman Garnett
Advances in Neural Information Processing Systems (NuerIPS 2019)
-
Backprop with Approximate Activations for Memory-efficient Network Training
with: Ayan Chakrabarti
Advances in Neural Information Processing Systems (NuerIPS 2019)
Project Page with Source Code
-
A Framework for Parallelizing Hierarchical Clustering Methods
with: Silvio Lattanzi, Thomas Lavastida, and Kefu Lu
European Conference on Machine Learning (ECML 2019)
-
On Functional Aggregate Queries with Additive Inequalities
with: Mahmoud Abo Khamis, Ryan Curtin, Hung Ngo, Long Nguyen, Dan Olteanu and Maximilian Schleich
ACM Symposium on Principals of Database Systems (PODS 2019)
-
Efficient Nonmyopic Batch Active Search
with: Shali Jiang, Gustavo Malkomes, Matthew Abbott, and Roman Garnett
Advances in Neural Information Processing Systems (NuerIPS 2018)
Spotlight Presentation.
- Approximation Bounds for Hierarchical Clustering: Average-Linkage, Bisecting K-means, and Local Search
with: Joshua Wang
Advances in Neural Information Processing Systems (NIPS 2017).
Oral Presentation
-
Efficient Nonmyopic Active Search
with: Shali Jiang, Gustavo Malkomes, Geoff Converse, Alyssa Shofner, and Roman Garnett
International Conference on Machine Learning (ICML 2017)
-
Efficient Massively Parallel Methods for Dynamic Programming
with: Sungjin Im and Xiaorui Sun
Symposium on Theory of Computing (STOC 2017)
-
Cooperative Set Function Optimization Without Communication or Coordination
with: Gustavo Malkomes, Kefu Lu, Blakeley Hoffman, Roman Garnett, and Richard Mann
Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017)
-
Local Search Methods for k-Means with Outliers
with: Shalmoli Gupta, Ravi Kumar, Kefu Lu and Sergei Vassilvitskii
International Conference on Very Large Data Bases (VLDB 2017)
-
Fast Distributed k-Center Clustering with Outliers on Massive Data
with: Gustavo Malkomes, Matt Kusner, Wenlin Chen, and Kilian Weinberger
Neural Information Processing Systems (NIPS 2015)
-
k-Means Clustering on Two-Level Memory Systems
with: Michael A. Bender, Jonathan Berry, Simon D. Hammond, Branden Moore, and Cynthia A. Phillips
International Symposium on Memory Systems (MEMSYS 2015)
-
Fast and Better Distributed MapReduce Algorithms for k-Center Clustering
with: Sungjin Im
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Brief Announcement
-
Two-Level Main Memory Co-Design: Multi-Threaded Algorithmic Primitives, Analysis, and Simulation
with: Michael A. Bender, Jonathan W Berry, Simon Hammond, Karl Hemmert, Samuel McCauley, Branden Moore, Cynthia A Phillips, David Resnick, and Arun Rodrigues
Awarded Best Paper
International Parallel and Distributed Processing Symposium (IPDPS 2015)
-
Fast Greedy Algorithms in MapReduce and Streaming
with: Ravi Kumar, Sergei Vassilvitskii and Andrea Vattani
Awarded Best Paper
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2013)
-
Scalable K-Means++
with: Bahman Bahmani, Andrea Vattani, Ravi Kumar and Sergei Vassilvitskii
International Conference on Very Large Data Bases (VLDB 2012)
-
Fast Clustering using MapReduce
with: Alina Ene and Sungjin Im
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2011) Oral Presentation.
-
Filtering: A Method for Solving Graph Problems in MapReduce
with: Silvio Lattanzi, Siddharth Suri and Sergei Vassilvitskii
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2011)
Resource Allocation:
-
Scheduling Out-Trees Online to Optimize Maximum Flow
with: Kunal Agrawal, Heather Newman, and Kirk Pruhs
Symposium on Parallel Algorithms and Architectures (SPAA 2024)
-
Controlling Tail Risk in Online Ski-Rental
with: Michael Dinitz, Sungjin Im, Thomas Lavastida, Sergei Vassilvitskii
ACM-SIAM Symposium on Discrete Algorithms (SODA 2024)
-
The Public University Secretary Problem
with: Heather Newman and Kirk Pruhs
SIAM Symposium on Simplicity in Algorithms (SOSA 2024)
-
Configuration Balancing for Stochastic Requests
with: Franziska Eberle, Anupam Gupta, Nicole Megow and Rudy Zhou
Conference on Integer Programming and Combinatorial Optimization (IPCO 2023)
-
Minimizing Completion Times for Stochastic Jobs via Batched
Free Times
with: Anupam Gupta and Rudy Zhou
ACM-SIAM Symposium on Discrete Algorithms (SODA 2023)
-
Online Scheduling of Parallelizable jobs in the Directed Acyclic Graphs and Speed-up Curves Models
with: Ruilong Zhang and Shanjiawen Zhao
Theoretical Compuer Science
-
On the Impossibility of Decomposing Binary Matroids
with: Marilena Leichter and Kirk Pruhs
Operations Research Letters (ORL)
-
A Competitive Algorithm for Throughout Maximization on Identical Machines
with: Kirk Pruhs, Clifford Stein, and Rudy Zhou
Conference on Integer Programming and Combinatorial Optimization (IPCO 2022)
-
Automatic HBM Management: Models and Algorithms
with: Kunal Agrawal, Michael Bender, Jonathan Berry, Rathish Das , Daniel DeLayo, Cynthia Phillips and Kenny Zhang
Symposium on Parallel Algorithms and Architectures (SPAA 2022)
-
The Efficiency-Fairness Balance of Round Robin Scheduling
with: Shai Vardi
Operations Research Letters (ORL)
-
The Case for Phase-Aware Scheduling
with: Benjamin Berg, Mor Harchol-Balter, Justin Whitehouse, Weina Wang
International Symposium on Computer Performance, Modeling, Measurements and Evaluation (Performance 2021)
-
An Efficient Reduction of a Gammoid to a Partition Matroid
with: Marilena Leichter and Kirk Pruhs
European Symposium on Algorithms (ESA 2021)
-
The Matroid Cup Game
with: Sungjin Im and Rudy Zhou
Operations Research Letters (ORL)
-
The Matroid Intersection Cover Problem
with: Sungjin Im and Kirk Pruhs
Operations Research Letters (ORL)
-
How to Manage High-Bandwidth Memory Automatically
with: Rathish Das, Kunal Agrawal, Michael Bender, Jonathan Berry, Benjamin Moseley and Cynthia Phillips
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020)
-
Optimal Resource Allocation for Elastic and Inelastic Jobs
with: Benjamin Berg, Mor Harchol-Balter, Justin Whitehouse, and Weina Wang
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020)
-
Dynamic Weighted Fairness with Minimal Disruptions
with: Sungjin Im, Kamesh Munagala, and Kirk Pruhs
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) (SIGMETRICS 2020)
-
Scheduling for Weighted Flow and Completion Times in Reconfigurable Networks
with: Michael Dinitz
IEEE International Conference on Computer Communications (INFOCOM 2020)
-
A Scheduling Approach to Incremental Maintenance of Datalog Programs
with: Shikha Singh, Sergey Madaminov, Michael Bender, Michael Ferdman, Ryan Johnson, Hung Ngo, Dung Nguyen, Soeren Olesen, Kurt Stirewalt, and Geoffrey Washburn
IEEE International Parallel and Distributed Processing Symposium (IPDPS 2020).
-
Online Non-preemptive Scheduling to Minimize Maximum Weighted Flow-time on Related Machines
with: Giorgio Lucarelli, Nguyen Thang, Abhinav Srivastav and Denis Trystram
Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)
-
SubmodularSubmodular Optimization with Contention Resolution Extensions
with: Maxim Sviridenko
International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2019)
-
Scheduling to Approximate Minimization Objectives on Identical Machines
with:
International Colloquium on Automata, Languages, and Programming (ICALP 2019)
-
Matroid Coflow Scheduling
with: Sungjin Im, Kirk Pruhs and Manish Purohit
International Colloquium on Automata, Languages, and Programming (ICALP 2019)
-
Practically Efficient Scheduler for Minimizing Average Flow Time of Parallel Jobs
with: Kunal Agrawal, I-Ting Angelina Lee, Jing Li and Kefu Lu
IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019)
-
Online Non-Preemptive Scheduling to Minimize Weighted Flow-time on Unrelated Machines
with: Giorgio Lucarelli, Nguyen Kim Thang, Abhinav Srivastav and Denis Trystram
European Symposium on Algorithms (ESA 2018)
-
Online Non-preemptive Scheduling on Unrelated Machines with Rejections
with: Giorgio Lucarelli, Nguyen Kim Thang, Abhinav Srivastav and Denis Trystram
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2018)
- Scheduling Parallelizable Jobs Online to Maximize Throughput
with: Kefu Lu, Kunal Agrawal, and Jing Li
Latin American Theoretical Informatics (LATIN 2018)
- An O(log log m)-competitive Algorithm for Online Machine Minimization
with: Sungjin Im, Kirk Pruhs and Clifford Stein
Real Time Systems Symposium (RTSS 2017)
- Minimizing Maximum Flow Time on Related Machines via Dynamic Posted Pricing
with: Sungjin Im, Kirk Pruhs and Clifford Stein
European Symposium on Algorithms (ESA 2017)
-
Scheduling Parallelizable Jobs Online to Maximize Throughput
with: Kunal Agrawal, Jing Li, and Kefu Lu
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2017) Brief Announcement
-
Breaking 1 - 1/e Barrier for Non-preemptive Throughput Maximization
with: Sungjin Im and Shi Li
Conference on Integer Programming and Combinatorial Optimization (IPCO 2017)
-
Stochastic Online Scheduling on Unrelated Machines
with: Varun Gupta, Marc Uetz and Qiaomin Xie
Conference on Integer Programming and Combinatorial Optimization (IPCO 2017)
A journal version is published at Mathematics of Operations Research. The paper contains an error and a correction with slightly looser bounds is published here.
-
Fair Scheduling via Iterative Quasi-Uniform Sampling
with: Sungjin Im
ACM-SIAM Symposium on Discrete Algorithms (SODA 2017)
-
A Competitive Flow Time Algorithm for Heterogeneous Clusters under Polytope ConstraintsM
with: Sungjin Im, Janardhan Kulkarni, and Kamesh Munagala
International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2016)
-
General Profit Scheduling and the Power of Migration on Heterogeneous Machines
with: Sungjin Im
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2016)
-
Scheduling Parallelizable Jobs Online to Minimize Maximum Flow Time
with: Kunal Agrawal, Jing Li, and Kefu Lu
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2016)
-
Partitioned Feasibility Tests for Sporadic Tasks on Heterogeneous Machines
with: Shaurya Ahuja and Kefu Lu
IEEE International Parallel & Distributed Processing Symposium (IPDPS 2016)
-
Scheduling Parallel DAG Jobs Online to Minimize Average Flow Time
with: Kunal Agrawal, Jing Li, and Kefu Lu
ACM-SIAM Symposium on Discrete Algorithms (SODA 2016)
-
Scheduling Parallel Jobs Online with Convex and Concave Parallelizability
with: Roozbeh Ebrahimi and Samuel McCauley
Workshop on Approximation and Online Algorithms (WAOA 2015)
-
Weighted Reordering Buffer Improved via Variants of Knapsack Covering Inequalities
with: Sungjin Im
International Colloquium on Automata, Languages, and Programming (ICALP 2015)
-
On the Randomized Competitive Ratio of Reordering Buffer Management with Non-Uniform Costs
with: Noa Avigdor-Elgrabli, Sungjin Im, and Yuval Rabani
International Colloquium on Automata, Languages, and Programming (ICALP 2015)
-
Temporal Fairness of Round Robin: Competitive Analysis for Lk-norms of Flow Time
with: Sungjin Im and Janardhan Kulkarni
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015)
-
Scheduling in Bandwidth Constrained Tree Networks
with: Sungjin Im
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015)
-
Stochastic Scheduling of Heavy-tailed Jobs
with: Sungjin Im and Kirk Pruhs
Symposium on Theoretical Aspects of Computer Science (STACS 2015)
-
A Dynamic Programming Framework for Non-Preemptive Scheduling Problems on Multiple Machines
with: Sungjin Im, Shi Li, and Eric Torng
ACM-SIAM Symposium on Discrete Algorithms (SODA 2015)
-
Competitively Scheduling Tasks with Intermediate Parallelizability
with: Sungjin Im, Kirk Pruhs, Eric Torng
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2014)
-
Scheduling to Minimize Energy and Flow Time in Broadcast Scheduling
with:
Journal of Scheduling
-
Packet Forwarding Algorithms in a Line Network
with: Antonios Antoniadis, Neal Barcelo, Daniel Cole, Kyle Fox, Michael Nugent and Kirk Pruhs
Latin American Theoretical Informatics Symposium (LATIN 2014)
-
Hallucination Helps: Energy Efficient Virtual Circuit Routing
with: Antonios Antoniadis, Sungjin Im, Ravishankar Krishnaswamy, Vishwanath Nagarajan, Kirk Pruhs and Cliff Stein
ACM-SIAM Symposium on Discrete Algorithms (SODA 2014)
-
New Approximations for Reordering Buffer Management
with: Sungjin Im
ACM-SIAM Symposium on Discrete Algorithms (SODA 2014)
-
Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions
with: Kyle Fox, Sungjin Im and Janardhan Kulkarni
International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2013).
-
Online Batch Scheduling for Flow Objectives
with: Sungjin Im
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2013) Brief Announcement
-
The Complexity of Scheduling for p-norms of Flow and Stretch
with: Kirk Pruhs and Cliff Stein
Conference on Integer Programming and Combinatorial Optimization (IPCO 2013)
-
Energy Efficient Scheduling of Parallelizable Jobs
with: Kyle Fox and Sungjin Im
ACM-SIAM Symposium on Discrete Algorithms (SODA 2013)
-
Shortest-Elapsed-Time-First on a Multiprocessor
with: Neal Barcelo, Sungjin Im and Kirk Pruhs
Mediterranean Conference on Algorithms (MedAlg 2012)
-
Speed Scaling for Total Stretch Plus Energy
with: Daniel Cole, Sungjin Im and Kirk Pruhs
Operations Research Letters
-
Online Scheduling with General Cost Functions
with: Sungjin Im and Kirk Pruhs
ACM-SIAM Symposium on Discrete Algorithms (SODA 2012)
-
Scheduling Heterogeneous Processors Isn't As Easy As You Think
with: Anupam Gupta, Sungjin Im, Ravishankar Krishnaswamy and Kirk Pruhs
ACM-SIAM Symposium on Discrete Algorithms (SODA 2012)
- A Tutorial on Amortized Local Competitiveness in Online Scheduling
with: Sungjin Im and Kirk Pruhs
A tutorial on the popular potential function technique for online scheduling problems.
ACM SIGACT News (June 2011)
- On Scheduling in Map-Reduce and Flow-Shops
with: Anirban Dasgupta, Ravi Kumar and Tamas Sarlos
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2011)
-
Online Scheduling on Identical Machines using SRPT
with: Kyle Fox
ACM-SIAM Symposium on Discrete Algorithms (SODA 2011)
-
Online Scalable Scheduling for the \ell_k-norms of Flow Time Without Conservation of Work
with: Jeff Edmonds and Sungjin Im
ACM-SIAM Symposium on Discrete Algorithms (SODA 2011)
- An Online Scalable Algorithm for Minimizing \ell_k-norms of Weighted Flow Time on Unrelated Machines
with: Sungjin Im
ACM-SIAM Symposium on Discrete Algorithms (SODA 2011)
- New Models and Algorithms for Throughput Maximization in
Broadcast Scheduling
with: Chandra Chekuri, Avigdor Gal, Sungjin Im, Samir Khuller, Jian Li, Richard McCutchen and Louiqa Raschid
Workshop on Approximation and Online Algorithms (WAOA 2010)
- Scheduling Jobs with Varying Parallelizability to Reduce Variance
with: Anupam Gupta, Sungjin Im, Ravishankar Krishnaswamy and Kirk Pruhs
ACM Symposium on Parallelism in Algorithms and Architectures
(SPAA 2010)
- An Online Scalable Algorithm for Average Flowtime in Broadcast Scheduling
with: Sungjin Im
Awarded Best Student Paper
ACM-SIAM Symposium on Discrete Algorithms (SODA 2010)
Journal Version: ACM Transactions on Algorithms
- Minimizing Maximum Response Time and Delay Factor in Broadcast Scheduling
with: Chandra Chekuri and Sungjin Im
European Symposium on Algorithms (ESA 2009)
Journal Version (Combines the results of this paper and the SODA 2009 paper below):
Theory of Computing: Special Issue in honor of Rajeev Motwani
- Longest Wait First For Broadcast Scheduling
with: Chandra Chekuri and Sungjin Im
Workshop on Approximation and Online Algorithms (WAOA 2009)
- Online Scheduling to Minimize the Maximum Delay Factor
with: Chandra Chekuri
ACM-SIAM Symposium on Discrete Algorithms (SODA 2009)
Energy Efficient Computing:
-
Scheduling to Minimize Energy and Flow Time in Broadcast Scheduling
with:
Journal of Scheduling
-
Hallucination Helps: Energy Efficient Virtual Circuit Routing
with: Antonios Antoniadis, Sungjin Im, Ravishankar Krishnaswamy, Vishwanath Nagarajan, Kirk Pruhs and Cliff Stein
ACM-SIAM Symposium on Discrete Algorithms (SODA 2014)
-
Energy Efficient Scheduling of Parallelizable Jobs
with: Kyle Fox and Sungjin Im
ACM-SIAM Symposium on Discrete Algorithms (SODA 2013)
-
Speed Scaling for Total Stretch Plus Energy
with: Daniel Cole, Sungjin Im and Kirk Pruhs
Operations Research Letters
-
Scheduling Heterogeneous Processors Isn't As Easy As You Think
with: Anupam Gupta, Sungjin Im, Ravishankar Krishnaswamy and Kirk Pruhs
ACM-SIAM Symposium on Discrete Algorithms (SODA 2012)
Web Advertising:
-
Bargaining for Revenue Shares on Tree Trading Networks
with: Arpita Ghosh, Satyen Kale, and Kevin Lang
International Joint Conference on Artificial Intelligence (IJCAI 2013) Oral Presentation and Poster
-
Handling Forecast Errors while Bidding for Display Advertising
with: Kevin Lang and Sergei Vassilvitskii
International Conference on World Wide Web (WWW 2012)
-
Scheduling Out-Trees Online to Optimize Maximum Flow