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.

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

deconstruct

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?

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.

9 pages in this format

(closed now)

This year, our workshop is motivated by the need for new means toto 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 wordinclude “” and “”. 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.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-- 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 You can contact us at: