Rohit Babbar

According to our database, Rohit Babbar authored at least 40 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Meta-classifier free negative sampling for extreme multilabel classification.

Mohammadreza Qaraei, Rohit Babbar

Mach. Learn., February, 2024

Consistent algorithms for multi-label classification with macro-at-k metrics.

Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski

CoRR, 2024

2023

Towards Memory-Efficient Training for Extremely Large Output Spaces - Learning with 500k Labels on a Single Commodity GPU.

Erik Schultheis, Rohit Babbar

CoRR, 2023

InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification.

Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta, Akash Palrecha, Rohit Babbar

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

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

Erik Schultheis, Rohit Babbar

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Generalized test utilities for long-tail performance in extreme multi-label classification.

Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Using ECCO-BERT and the Historical Thesaurus of English to Explore Concepts and Agency in Historical Writing Interpreting the Eighteenth-century Luxury Debate.

Aatu Liimatta, Eetu Mäkelä, Filip Ginter, Iiro Rastas, Iiro Tiihonen, Jinbin Zhang, Lidia Pivovarova, Mikko Tolonen, Milja K, Rohit Babbar, Ruilin Wang, Tanja Säily, Yann Ciarán Ryan

Proceedings of the Annual International Conference of the Alliance of Digital Humanities Organizations, 2023

2022

Speeding-up one-versus-all training for extreme classification via mean-separating initialization.

Erik Schultheis, Rohit Babbar

Mach. Learn., 2022

Adversarial examples for extreme multilabel text classification.

Mohammadreza Qaraei, Rohit Babbar

Mach. Learn., 2022

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

Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification.

Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Detecting Sequential Genre Change in Eighteenth-Century Texts.

Jinbin Zhang, Yann Ciarán Ryan, Iiro Rastas, Filip Ginter, Mikko Tolonen, Rohit Babbar

Proceedings of the Computational Humanities Research Conference 2022, 2022

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

Iiro Rastas, Yann Ciarán Ryan, Iiro Tiihonen, Mohammadreza Qaraei, Liina Repo, Rohit Babbar, Eetu Mäkelä, Mikko Tolonen, Filip Ginter

Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, 2022

Extreme Multicore Classification.

Erik Schultheis, Rohit Babbar

Proceedings of the Machine Learning under Resource Constraints - Volume 1: Fundamentals, 2022

2021

Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization.

Erik Schultheis, Rohit Babbar

CoRR, 2021

Unbiased Loss Functions for Multilabel Classification with Missing Labels.

Erik Schultheis, Rohit Babbar

CoRR, 2021

Embedding Convolutions for Short Text Extreme Classification with Millions of Labels.

Siddhant Kharbanda, Atmadeep Banerjee, Akash Palrecha, Rohit Babbar

CoRR, 2021

Convex Surrogates for Unbiased Loss Functions in Extreme Classification With Missing Labels.

Mohammadreza Qaraei, Erik Schultheis, Priyanshu Gupta, Rohit Babbar

Proceedings of the WWW '21: The Web Conference 2021, 2021

Propensity-scored Probabilistic Label Trees.

Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczynski

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

2020

Bonsai: diverse and shallow trees for extreme multi-label classification.

Sujay Khandagale, Han Xiao, Rohit Babbar

Mach. Learn., 2020

Unbiased Loss Functions for Extreme Classification With Missing Labels.

Erik Schultheis, Mohammadreza Qaraei, Priyanshu Gupta, Rohit Babbar

CoRR, 2020

Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading.

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

Proceedings of the 39th IEEE Conference on Computer Communications, 2020

Neural Architecture Search for Extreme Multi-label Text Classification.

Loïc Pauletto, Massih-Reza Amini, Rohit Babbar, Nicolas Winckler

Proceedings of the Neural Information Processing - 27th International Conference, 2020

Why state-of-the-art deep learning barely works as good as a linear classifier in extreme multi-label text classification.

Mohammadreza Qaraei, Sujay Khandagale, Rohit Babbar

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Data scarcity, robustness and extreme multi-label classification.

Rohit Babbar, Bernhard Schölkopf

Mach. Learn., 2019

A Simple and Effective Scheme for Data Pre-processing in Extreme Classification.

Sujay Khandagale, Rohit Babbar

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018

Adversarial Extreme Multi-label Classification.

Rohit Babbar, Bernhard Schölkopf

CoRR, 2018

2017

DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification.

Rohit Babbar, Bernhard Schölkopf

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

2016

Learning Taxonomy Adaptation in Large-scale Classification.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard

J. Mach. Learn. Res., 2016

TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification.

Rohit Babbar, Krikamol Muandet, Bernhard Schölkopf

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

2015

Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data.

Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

2014

Machine Learning Strategies for Large-scale Taxonomies. (Strategies d'apprentissage pour la classification dans les grandes taxonomies).

Rohit Babbar

PhD thesis, 2014

On power law distributions in large-scale taxonomies.

Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

SIGKDD Explor., 2014

Re-ranking approach to classification in large-scale power-law distributed category systems.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

2013

On Flat versus Hierarchical Classification in Large-Scale Taxonomies.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

Proceedings of the Neural Information Processing - 20th International Conference, 2013

Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law.

Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Éric Gaussier, Massih-Reza Amini

Proceedings of the Semantic Web: ESWC 2013 Satellite Events, 2013

2012

Adaptive Classifier Selection in Large-Scale Hierarchical Classification.

Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard

Proceedings of the Neural Information Processing - 19th International Conference, 2012

On empirical tradeoffs in large scale hierarchical classification.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2010

Clustering based approach to learning regular expressions over large alphabet for noisy unstructured text.

Rohit Babbar, Nidhi Singh

Proceedings of the Fourth Workshop on Analytics for Noisy Unstructured Text Data, 2010