Rohit Babbar
Visitor
Visitor
T313 Dept. Computer Science
I am an Assistant Professor at the department of Computer Science, Aalto University in Finland. Along with my research group, we work on problems in large scale machine learning particularly encountered in extreme classification with large output spaces, and robustness
Full researcher profile
https://research.aalto.fi/...
Sähköposti
ext-rohit.babbar@aalto.fi
Puhelinnumero
+358505122646
Osaamisalueet
large scale learning, extreme multi-label classification, deep learning, sequential data, robustness
Palkinnot
Outstanding Reviewer Award ACL 2021 Conference
Award or honor granted for a specific work
Computer Science Professors
Jul 2021
Tutkimusryhmät
- Professorship Marttinen P., Assistant Professor
Julkaisut
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification
Siddhant Kharbanda, Devaansh Gupta, K. Gururaj, Pankaj Malhotra, Amit Singh, Cho Jui Hsieh, Rohit Babbar
2025
WWW 2025 - Proceedings of the ACM Web Conference
How Well Calibrated are Extreme Multi-label Classifiers? An Empirical Analysis
Nasib Ullah, Erik Schultheis, Jinbin Zhang, Rohit Babbar
2025
KDD 2025 : Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Nasib Ullah, Erik Schultheis, Mike Lasby, Yani Ioannou, Rohit Babbar
2025
Advances in Neural Information Processing Systems 37 (NeurIPS 2024)
Large Language Model as a Teacher for Zero-shot Tagging at Extreme Scales
Jinbin Zhang, Nasib Ullah, Rohit Babbar
2025
The 31st International Conference on Computational Linguistics (COLING 2025)
Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features
Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho Jui Hsieh, Rohit Babbar
2024
KDD 2024 - Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
A General Online Algorithm for Optimizing Complex Performance Metrics
Wojciech Kotłowski, Marek Wydmuch, Erik Schultheis, Rohit Babbar, Krzysztof Dembczyński
2024
Proceedings of Machine Learning Research
Meta-classifier free negative sampling for extreme multilabel classification
Mohammadreza Mohammadnia Qaraei, Rohit Babbar
2024
Machine Learning
Consistent algorithms for multi-label classification with macro-at-k metrics
Erik Schultheis, Wojciech Kotłowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczyński
2024
12th International Conference on Learning Representations (ICLR 2024)
Generalized test utilities for long-tail performance in extreme multi-label classification
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski
2024
Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023
InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification
Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta, Akash Palrecha, Rohit Babbar
2023
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval