Workshop Program [slides]

8:30Welcome & Opening remarks

8:45Keynote Presentation (abstract)
'Making sense of unusual suspects - Finding and Characterizing Outliers'

by Ira Assent

9:30 Coffee

10:00Keynote Presentation (abstract)
'The Outlier Description Problem - Complexity Results, Declarative Formulations and Applications '

by Ian Davidson

10:45 Contributed papers (see list) (10+5 minutes each)

12:00 Lunch

13:00Keynote Presentation (abstract)
'Outlier Description and Interpretation'

by Jian Pei

13:45 Invited papers from KDD track (see list) (10+5 minutes each)

14:30 Coffee

15:00Keynote Presentation (abstract)
'Outlier Detection for Mining Social Misbehavior'

by Neil Shah

15:45 Contributed papers (see list) (10+5 minutes each)

17:00 Spotlight talks for poster papers (see list) (2 minutes each)

17:10 Poster session (for all contributed and poster papers)

18:00 Closing

ODD v5.0 is a full day workshop, organized in conjunction with ACM SIGKDD 2018.
We build on the successful series of past four ODD Workshops that have been organized:
ODD 4.0 @KDD 2016, ODDx3 @KDD 2015, ODD^2 @KDD 2014, and ODD @KDD 2013.

The main goal of the ODD workshop is to bring together academics, industry and government researchers and practitioners to discuss and reflect on recent outlier mining challenges.

Keynote Speakers

speaker speaker speaker speaker
Ira Assent
Associate Professor
Aarhus U.
      Ian Davidson
UC Davis
      Jian Pei
Professor, Simon Fraser
     Neil Shah
Research Scientist
Snap Inc.

Important Dates

Submission Deadline [ EasyChair Submission Link ] May 15, 2018, 11:59 PM PST
Notification to Authors June 22, 2018, 11:59 PM PST
Camera-ready Deadline June 29, 2018, 11:59 PM PST
Workshop day August 20, 2018

Outlier Detection De-constructed

This year, our workshop is motivated by the need for new means to de-construct the black-box nature of outlier detection methods to offer solutions for predictions to be interpreted, adopted, trusted, and safely used by decision makers in mission-critical applications. Roughly speaking, by de-construction we mean the process of tracing the contribution of each input to the output (for a given example) and evaluate to which extent a particular input would move the output due to inherited variations.

The glossary definitions of the word deconstruct include “analyze (a text or a linguistic or conceptual system) by deconstruction, typically in order to expose its hidden internal assumptions and contradictions and subvert its apparent significance or unity” and “reduce (something) to its constituent parts in order to reinterpret it”. This is exactly what the ODD v5.0 workshop focuses on in the context of outlier mining, that is, identifying the constituent parts of a detection model to expose its hidden/underlying reasoning to flag an outlier.

In short, ODD v5.0 (2018) aims to increase awareness of the community to the following topics on outlier mining.

      • How can we (verbally or visually) explain the reasoning behind the decisions of various outlier detection models?
      • What is the extent to which we can draw causal (i.e. beyond descriptive) explanations to the emergence of outliers?
      • What techniques can be used for identifying root causes and generating mechanisms of outliers for diagnosis and treatment?
      • How can we leverage interactions with human experts to mine outliers?
      • How can we incorporate complex user feedback for outlier detection?
      • How can we employ novel deep learning models for outlier detection?
      • How can we create an ensemble of outlier detectors that is interpretable?
      • How can we apply recurrent models to outlier detection in complex data such as graph or text data streams?
      • How can we design explanation techniques for complex detectors such as deep models as well as ensemble detection methods?

Call for Papers

While we aim for a focus on the theme of explanations (for complex models), we welcome papers addressing any other challenges at large of the subject area. Topics of interests for the workshop include, but are not limited to:

Submission Guidelines

We invite submission of original research papers as well as relevant work that has previously been published, including papers in the main track of the KDD conference. We also invite work-in-progress papers, papers on case studies on benchmark data, as well as demo papers.

All papers will be peer reviewed. If accepted, at least one of the authors must attend the workshop to present the work. The submitted papers must be written in English and formatted according to the ACM Proceedings Template (Tighter Alternate style). The maximum length of papers is 9 pages in this format -- shorter papers are also welcome. The paper submission should be in PDF.

The accepted papers will be published on the workshop's website, and will not be considered archival for resubmission purposes.

Please submit your papers at the EasyChair Submission Link (closed now).

Program Committee


You can contact us at:
oddv5.0 (at)