Workshop Program

13:15Welcome & Remarks

13:30Keynote Presentation (abstract)
Moving from Anomalies to Known Phenomena
by Jeff Schneider

14:30 Research talks (15+5 minutes each)
  • Dealing with Class Imbalance using Thresholding
    Charmgil Hong, Rumi Ghosh and Soundar Srinivasan.
  • Generating Local Explanations of Network Anomalies via Score Decomposition
    Timothy La Fond, Jennifer Neville and Brian Gallagher.
  • Fast and Accurate Kmeans Clustering with Outliers
    Shalmoli Gupta.

15:30 Coffee

16:00 Research talks (15+5 minutes each)
  • Detection of Cyber-Physical Faults and Intrusions from Physical Correlations
    Andrey Lokhov, Nathan Lemons, Thomas McAndrew, Aric Hagberg and Scott Backhaus.
  • Interpretable Anomaly Detection for Monitoring of High Performance Computing Systems
    Elisabeth Baseman, Sean Blanchard, Nathan Debardeleben, Amanda Bonnie and Adam Morrow.
  • Beauty and Brains: Detecting Anomalous Pattern Co-Occurrences
    Roel Bertens, Jilles Vreeken and Arno Siebes.

17:00 Closing

ODD 4.0 is a half-day workshop, organized in conjunction with ACM SIGKDD 2016.
We follow the successful series of three ODD Workshops that have been organized at ACM KDD 2015, KDD 2014, and KDD 2013.

Outlier Definition, Detection, and Description on Demand

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

The ODD (2013) Workshop focused on outlier detection and description, with particular emphasis on descriptive methods that could help make sense of the detected outliers. Next, ODD^2 (2014) extended the focus areas to outlier detection and description under data diversity, with emphasis on challenges associated with mining outliers in heterogeneous data environments (graphs, text, streams, metadata, etc.). ODDx3 (2015) focused on the translation of real world applications to different outlier definitions, highlighting the challenges associated with the variety of outlier definitions defined in theoretic models and used in a multitude of application domains.

This year, thanks to the feedback of industrial attendees at last year’s ODD workshop, we broaden the scope to industrial challenges (e.g. known from Industry 4.0 initiatives) for on-demand computation, visualization, and verification of outliers in industrial settings. This includes open challenges for (1) online stream outlier mining, (2) real-time visualization of anomalies, and (3) interactive exploration of outlier instances. Overall, ODD 4.0 (2016) aims to increase awareness of the community to the following challenges of outlier mining:

      • What are the key outlier mining requirements in industry?
      • How can we define outliers in data streams?
      • How can online detection and description be supported?
      • How can applications (e.g. predictive maintenance) steer outlier search?
      • How can we compute real-time visualizations of outlier models?
      • How could interaction allow better and more intuitive outlier mining?

Invited Speakers

We are proud to have Dr. Jeff Schneider as our keynote speaker.

Jeff Schneider is currently the engineering lead at Uber ATC and an associate research professor at the School of Computer Science of Carnegie Mellon University. He received his PhD in Computer Science from the University of Rochester in 1995. He has over 15 years experience developing, publishing, and applying machine learning algorithms in government, science, and industry. He has dozens of publications and has given numerous invited talks and tutorials on the subject.
Dr. Schneider was the co-founder and CEO of Schenley Park Research,Inc. (SPR), a company dedicated to bringing new machine learning algorithms to industry. Later, he developed a new machine-learning based CNS drug discovery system and spent a two-year sabbatical as the Chief Informatics Officer of a biotech, Psychogenics, to set up and commercialize the system. Through his work at CMU and his commercial and consulting efforts, he has worked with several dozen companies and government agencies including six Fortune 500 companies, and groups from seven other countries.

The keynote will be 55 minutes long, including questions.

Important Dates

Submission Deadline May 27, 2016, 23:59 PST
Notification to Authors June 16, 2016, 23:59 PST
Camera-ready Deadline July 1, 2016, 23:59 PST
Workshop day August 14, 2016

Call for Papers

Topics of interests for the workshop include, but are not limited to:

Submission Guidelines

We invite submission of unpublished original research papers that are not under review elsewhere. 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 10 pages in this format. We also invite vision papers and descriptions of work-in-progress or case studies on benchmark data as short paper submissions of up to 4 pages. The papers should be in PDF format.

Please submit your papers at the EasyChair Submission Link.

Submission is closed.

Program Committee (Tentative)

  • Fabrizio Angiulli (University of Calabria)
  • James Bailey (University of Melbourne)
  • Arindam Banerjee (University of Minnesota)
  • Albert Bifet (Télécom ParisTech)
  • Petko Bogdanov (SUNY Albany)
  • Christian Böhm (University of Munich)
  • Rajmonda Caceres (MIT)
  • Varun Chandola (SUNY Buffalo)
  • Sanjay Chawla (University of Syndey)
  • Feng Chen (SUNY Albany)
  • Thomas Dietterich (Oregon State University)
  • Shobeir Fakhraei (University of Maryland)
  • Jaakko Hollmén (Aalto University)
  • Daniel Keim (University of Konstanz)
  • Arun Maiya (Institute for Defense Analyses)
  • Julian McAuley (UC San Diego)
  • Raymond Ng (University of British Columbia)
  • Lionel Ott (University of Sydney)
  • Spiros Papadimitriou (Rutgers)
  • Ambuj Singh (UC Santa Barbara)
  • Hanghang Tong (Arizona State)
  • Matthijs van Leeuwen (Universiteit Leiden)
  • Weng-Keen Wong (Oregon State University)


You can contact us at:
odd16kdd (at)