Nicolas Goix – Papers

Papers

• One Class Splitting Criteria for Random Forests [arXiv]
  N. Goix, R. Brault, N. Drougard, M. Chiapino (ACML 2017)

• How to Evaluate the Quality of Unsupervised Anomaly Detection Algorithms? [arXiv]
  N. Goix (ICML 2016, Workshop on Anomaly Detection, co-winner of Google Best Paper Award)

• Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking. [JMLR]
  N. Goix, A. Sabourin, S. Clémençon (AISTAT 2016)

• Sparse Representation of Multivariate Extremes. [PDF]
  N. Goix, A. Sabourin, S. Clémençon (NIPS Workshop on Nonparametric Methods for Large Scale Representation Learning, 2015)

• Sparsity in Multivariate Extremes with Application to Anomaly Detection. [ArXiv]
  N. Goix, A. Sabourin, S. Clémençon (Journal of Multivariate Analysis 2017)

• Learning the Dependence Structure of Rare Events: a Non-Asymptotic Study. [JMLR]
  N. Goix, A. Sabourin, S. Clémençon (COLT 2015, selected for a long talk)

• On Anomaly Ranking and Excess-Mass Curves. [JMLR]
  N. Goix, A. Sabourin, S. Clémençon (AISTAT 2015)

PhD Thesis

• Machine Learning and Extremes for Anomaly Detection. [online] [book]
  N. Goix (Dec. 2016)

Talks and Resources

• UMPC LSTA GT Extremes, Machine Learning and Extremes for Anomaly Detection [Slides]

• ICML 2016, Workshop on Anomaly Detection , New York City June 2016, how to evaluate anomaly detection algorithms? [Slides]

• AISTATS 2016, Cadiz May 2016 , Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking

• French Ministry of Industry, Bourse aux Technologies--Industrie du Futur--Smart Manufacturing , Paris Mars 2016, Damex: Detecting Anomalies in High Dimension.

• Telecom Paristech, TSI department seminar, Paris Jan. 2016, Anomaly Detection in Scikit-Learn and new tools from Multivariate Extreme Value Theory. [Slides]

• NIPS 2015, Workshop on Nonparametric Methods for Large Scale Representation Learning, Montréal Dec. 2015, Sparse Representation of Multivariate Extremes [Poster]

• Séminaire LJK-Statistique, Grenoble Nov. 2015, Learning a Sparse Representation of Rare Events with Application to Anomaly Ranking [Slides]

• Paris-Saclay Center for Data Science, Orsay Oct. 2015, Anomaly Detection algorithms in Scikit-Learn [Video talk with slides] [Slides]

• ML for Big Data Chair - GT predictive maintenance, Paris Oct. 2015, Anomaly Detection with Multivariate Extremes [Slides]

• COLT 2015, Paris July 2015, Learning the Dependence Structure of Rare Events [Video talk with slides] [Slides][Poster]

• AISTAT 2015, San Diego May 2015, Anomaly Ranking and Excess-Mass Curves [Poster]

• Séminaire de Statistique AgroParisTech, Paris May 2015, Scoring Anomalies among Multivariate Extreme Observations [Slides]

• SMILE, 'NIPS defriefing', Paris January 15, Approximating Hierarchical MV-sets for Hierarchical Clustering (Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch)