Hello, I am an Associate Professor (Senior Lecturer) at the Computer Science department of the University of Bath, UK, and a visiting Professor at Aalto University, Finland. I work on large-scale machine learning problems particularly in Extreme Classification and learning with imperfect supervision. Looking for motivated research assistants, please email 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
Selected Publications (All publications on google scholar)
Consistent Algorithms for Multi-label Classification with Macro@k Metrics
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Strom Borman, and Krzysztof Dembczyński
12th International Conference on Learning Representations, ICLR 2024, Vienna, AustriaGeneralized Test Utilities for Long-tail Performance in Extreme Multi-label Classification
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, and Krzysztof Dembczyński
37th Conference on Neural Information Processing Systems, NeurIPS, 2023, New Orleans, USATowards Memory-Efficient Training for Extremely Large Output Spaces -- Learning with 500k Labels on a Single Commodity GPU
Erik Schultheis, Rohit Babbar
ECML-PKDD 2023, (arXiv pre-print), Torino, ItalyInceptionXML : A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification (pdf , code )
Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta, Akash Palrecha, and Rohit Babbar
46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, TaiwanCascadeXML : Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-Label Classification (pdf , code),
Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis and Rohit Babbar
36th Conference on Neural Information Processing Systems, NeurIPS, 2022, New Orleans, USAOn Missing Labels, Long tails and propensities in Extreme Multi-label Classification (pdf , code)
Erik Schultheis, Marek Wydmuch, Rohit Babbar, and Krzysztof Dembczyński
28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022, Washington, USAAdversarial Examples for Extreme Multi-label Classification, (pdf, code)
Mohamaadreza Qaraei, Rohit Babbar, Machine Learning Journal 2022Speeding-up One-vs-All Training for Extreme Classification via Mean-separating Initialization, (pdf, Code)
Erik Schultheis, and Rohit Babbar
ECML & Machine Learning Journal Track, ECML-MLJ, 2022Convex Surrogates for Unbiased Loss Functions in Extreme Classification With Missing Labels (pdf, video, code)
Mohammadreza Qaraei, Erik Schultheis, Priyanshu Gupta, Rohit Babbar
30th ACM International World Wide Web Conference, The WebConf (WWW) 2021
Teaching
Kernel Methods in Machine Learning (5 ECTS, Spring 2019, 2020, 2021)
Introduction to Data Science (Bachelor level, 5 ECTS, Fall 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