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
- Our research is supported by Criteo Faculty Research Grant. Thanks to Criteo!
- I will be participating in the Dagstuhl seminars on Extreme Classification in July 2018.
- With Krzysztof Dembczyński, I am co-organizing a tutorial on Extreme Classification at ECIR 2018, Grenoble.
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
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
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 :
- Researcher at the Empirical Inference group headed by Prof. Bernhard Schölkopf (2015 - 2017), at Max-Planck Institute for Intelligent Systems, Tübingen, Germany
- Doctoral Degree in Computer Science from University of Grenoble Alpes, (2011-2014) advised by Prof. Eric Gaussier and Prof. Massih-Reza Amini.
- Master in Computer Science, 2009-2011, from Chennai Mathematical Institute, India. Did my master thesis (Jan-June, 2011) under supervision of Dr. Manik Varma and Prof. Madhavan Mukund
Other Stuff
- Long ago, finished Grenoble-Vizille Semi-marathon