Personer

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/...
E-post
[email protected]
Telefonnummer
+358505122646

Kompetensområde

large scale learning, extreme multi-label classification, deep learning, sequential data, robustness

Utmärkelser

Outstanding Reviewer Award ACL 2021 Conference

Award or honor granted for a specific work Computer Science Professors Jul 2021

Publikationer

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

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

Extreme Multicore Classification

Erik Schultheis, Rohit Babbar 2023 Machine Learning under Resource Constraints

Towards Memory-Efficient Training for Extremely Large Output Spaces : Learning with 670k Labels on a Single Commodity GPU

Erik Schultheis, Rohit Babbar 2023 Machine Learning and Knowledge Discovery in Databases

CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification

Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar 2022 Advances in Neural Information Processing Systems 35 (NeurIPS 2022)

Adversarial examples for extreme multilabel text classification

Mohammadreza Mohammadnia Qaraei, Rohit Babbar 2022 Machine Learning

Explainable Publication Year Prediction of Eighteenth Century Texts with the BERT Model

Iiro Rastas, Yann Ciarán Ryan, Iiro Tiihonen, Mohammadreza Mohammadnia Qaraei, Liina Repo, Rohit Babbar, Eetu Mäkelä, Mikko Tolonen, Filip Ginter 2022 Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change