Rohit Babbar

Hello, I am an Assistant Professor at the department of Computer Science, Aalto University in Finland. I work on problems in large-scale machine learning, shallow and deep Learning for extreme classification, and robustness of machine learning models.

I am looking for students interested in doing PhD or Master's thesis in the above or related areas. Please do not hesitate to contact at firstname.lastname_at_aalto.fi.

Extreme Classification Repository - Maintained by Manik Varma, consists of Datasets and (links to) code for most recent methods for extreme classification


News

Publications:

2018

  • Adversarial Extreme Multi-label Classification pdf

Rohit Babbar and Bernhard Schölkopf

Rohit Babbar, Martin Heni, Andreas Peter, Martin Hrabě de Angelis, Hans-Ulrich Häring, Andreas Fritsche, Hubert Preissl, Bernhard Schölkopf, Róbert Wagner

Frontiers in Endocrinology

2017

  • DiSMEC : Distributed Sparse Machines for Extreme Multi-label Classification, pdf Code

Rohit Babbar and Bernhard Schölkopf

ACM International Conference on Web Search and Data Mining (WSDM) 2017, Cambridge;

Also accepted for NIPS 2016 Extreme Classification Workshop

2016

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

Journal of Machine Learning Research , (JMLR 2016)

  • TerseSVM : A scalable approach for learning compact models in Large-scale classification

Rohit Babbar, Krikamol Muandet, and Bernhard Schölkopf

SIAM International Conference on Data Mining (SDM 2016), Miami

2015

  • Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data

Georgios Balikas, Ioannis Partalas, Eric Gaussier, Rohit Babbar and Massih-Reza Amini

International Symposium on Intelligent Data Analysis, (IDA 2015), Saint-Etienne, France

2014

  • Re-ranking Approach to Classification in Large-scale Power-law Distributed Category Systems, pdf

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

ACM SIGIR Conference , (SIGIR 2014), Gold Coast, Australia,

  • On Power Law Distributions in Large-scale Taxonomies", pdf

Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

SIGKDD Explorations Journal, Special Issue on Big Data

2013

  • On Flat versus Hierarchical Classification in Large-Scale Taxonomies", pdf

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

Neural Information Processing Systems, (NIPS 2013), Lake Tahoe, Neveda, USA

  • Maximum-margin Framework for Training Data Synchronization in Large-scale Hierarchical Classification, pdf,

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

Intl. Conference on Neural Information Processing, (ICONIP 2013), Daegu, Korea

  • Comparative Classifier Evaluation for Web-scale Taxonomies using Power Law,

Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Eric Gaussier and Massih-reza Amini

European Semantic Web Conference (ESWC 2013), Montpiller, France.

2012

  • On Empirical Tradeoffs in Large Scale Hierarchical Classification,

Rohit Babbar, Ioannis Partalas, Eric Gaussier, Cecile Amblard

ACM Intl. Conference on Information and Knowledge Management, (CIKM 2012), Maui, Hawaii.

  • Adaptive Classifier Selection in Large-scale Hierarchical Classification,

Ioannis Partalas, Rohit Babbar, Eric Gaussier, Cecile Amblard

Intl. Conference on Neural Information Processing, (ICONIP 2012), Doha, Qatar.

Academic Trail :

Talks :

  • Magnet Team, INRIA, Lille, January 2017
  • ABC Team, LORIA, Nancy, November, 2016
  • Big Data for Material Sciences Workhsop, Ringberg Castle, July 2016
  • Data Analytics Lab, ETH Zurich, November 2015
  • Bosch Corporate Research Center, Renningen, October 2015
  • Magnet Team, INRIA, Lille, December 2014

Other Talks/Poster Presentations :

  • WSDM 2017, Cambridge
  • NIPS XMC workshop 2016, Barcelona
  • SDM 2016, Miami
  • SIGIR 2014, Gold Coast
  • NIPS 2013, Lake Tahoe
  • ICONIP 2013, Daegu
  • CIKM 2012, Hawaii

Other Stuff

- Long ago, finished Grenoble-Vizille Semi-marathon