Hello, I am an Assistant Professor in the department of Computer Science, Aalto University at Helsinki, Finland. In my team, we work on large-scale machine learning problems particularly in Extreme Classification and robustness. I am looking for research assistants to work on the problems in these areas. If interested, please contact at firstname.lastname@aalto.fi

Before this, I was a post-doc at Max-Planck Institute for Intelligent Systems, Tuebingen, Germany in the group of Prof. Bernhard Schölkopf. I finished my PhD from University of Grenoble, France where I was advised by Prof. Eric Gaussier and Prof. Massih-Reza Amini

News

Selected Publications (All publications on google scholar) :

  • Unbiased Loss Functions for Extreme Classification With Missing Labels pdf

Erik Schultheis, Mohammadreza Qaraei, Priyanshu Gupta, Rohit Babbar

ICML 2020 workshop on Extreme Classification

  • Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading pdf

Mohammed Thaha, Carlee Joe-Wong, Rohit Babbar, Mario Di Francesco

20th IEEE International Conference on Computer Communications, Infocom 2020


  • Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification pdf

Code Rust implementation by Tom Dong Datasets

Sujay Khandagale, Han Xiao, Rohit Babbar

Machine Learning Journal 2020


  • Data Scarcity, Robustness and Extreme Multi-label Classification pdf

Code, Datasets

Rohit Babbar and Bernhard Schölkopf

Machine Learning Journal and European Conference on Machine Learning (ECML) 2019


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

Code Datasets

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


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


  • 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


  • 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

Teaching

  • Kernel Methods in Machine Learning (5 ECTS, Jan - April 2019)
  • Supervised Learning with Large Label Sets ( 3 ECTS, Spring 2018)

Reviewing activities :

  • 2019 - AAAI, ICLR, AISTATS, ICML, NIPS, IJCAI, JMLR, MLJ
  • 2018 - NIPS, ICML, ICLR, AISTATS, AAAI, JMLR, IEEE PAMI
  • 2017 - NIPS, ICML, ICLR, AISTATS

Academic Trail :


Other Stuff

- Long ago, finished Grenoble-Vizille Semi-marathon