Rohit Babbar

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 42

Top Venues

Grenoble Alpes University, France (PHD)

Education History

Grenoble Alpes University, France

PHD

Publications

Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features. KDD (2024)
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski
Consistent algorithms for multi-label classification with macro-at-k metrics. ICLR (2024)
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski
Consistent algorithms for multi-label classification with macro-at-k metrics. CoRR (2024)
Jinbin Zhang, Nasib Ullah, Rohit Babbar
Zero-Shot Learning Over Large Output Spaces : Utilizing Indirect Knowledge Extraction from Large Language Models. CoRR (2024)
Mohammadreza Qaraei, Rohit Babbar
Meta-classifier free negative sampling for extreme multilabel classification. Mach. Learn. 113 (2) (2024)
Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
Learning label-label correlations in Extreme Multi-label Classification via Label Features. CoRR (2024)
Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Cho-Jui Hsieh, Rohit Babbar
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification. CoRR (2024)
Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis, Rohit Babbar, Krzysztof Dembczynski
A General Online Algorithm for Optimizing Complex Performance Metrics. CoRR (2024)
Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta, Akash Palrecha, Rohit Babbar
InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification. SIGIR (2023)
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
Using ECCO-BERT and the Historical Thesaurus of English to Explore Concepts and Agency in Historical Writing Interpreting the Eighteenth-century Luxury Debate. DH (2023)
Erik Schultheis, Rohit Babbar
Towards Memory-Efficient Training for Extremely Large Output Spaces - Learning with 500k Labels on a Single Commodity GPU. CoRR (2023)
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski
Generalized test utilities for long-tail performance in extreme multi-label classification. CoRR (2023)
Erik Schultheis, Rohit Babbar
Towards Memory-Efficient Training for Extremely Large Output Spaces - Learning with 670k Labels on a Single Commodity GPU. ECML/PKDD (3) (2023)
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski
Generalized test utilities for long-tail performance in extreme multi-label classification. NeurIPS (2023)
Erik Schultheis, Rohit Babbar
Speeding-up one-versus-all training for extreme classification via mean-separating initialization. Mach. Learn. 111 (11) (2022)
Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification. NeurIPS (2022)
Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification. CoRR (2022)
Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification. CoRR (2022)
Iiro Rastas, Yann Ciarán Ryan, Iiro Tiihonen, Mohammadreza Qaraei, Liina Repo, Rohit Babbar, Eetu Mäkelä, Mikko Tolonen, Filip Ginter
Explainable Publication Year Prediction of Eighteenth Century Texts with the BERT Model. LChange@ACL (2022)
Mohammadreza Qaraei, Rohit Babbar
Adversarial examples for extreme multilabel text classification. Mach. Learn. 111 (12) (2022)
Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification. KDD (2022)
Jinbin Zhang, Yann Ciarán Ryan, Iiro Rastas, Filip Ginter, Mikko Tolonen, Rohit Babbar
Detecting Sequential Genre Change in Eighteenth-Century Texts. CHR (2022)
Siddhant Kharbanda, Atmadeep Banerjee, Akash Palrecha, Rohit Babbar
Embedding Convolutions for Short Text Extreme Classification with Millions of Labels. CoRR (2021)
Mohammadreza Qaraei, Rohit Babbar
Adversarial Examples for Extreme Multilabel Text Classification. CoRR (2021)
Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczynski
Propensity-scored Probabilistic Label Trees. CoRR (2021)
Erik Schultheis, Rohit Babbar
Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization. CoRR (2021)
Erik Schultheis, Rohit Babbar
Unbiased Loss Functions for Multilabel Classification with Missing Labels. CoRR (2021)
Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczynski
Propensity-scored Probabilistic Label Trees. SIGIR (2021)
Mohammadreza Qaraei, Erik Schultheis, Priyanshu Gupta, Rohit Babbar
Convex Surrogates for Unbiased Loss Functions in Extreme Classification With Missing Labels. WWW (2021)
Thaha Mohammed, Carlee Joe-Wong, Rohit Babbar, Mario Di Francesco
Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading. INFOCOM (2020)
Loïc Pauletto, Massih-Reza Amini, Rohit Babbar, Nicolas Winckler
Neural Architecture Search for Extreme Multi-label Text Classification. ICONIP (3) (2020)
Mohammadreza Qaraei, Sujay Khandagale, Rohit Babbar
Why state-of-the-art deep learning barely works as good as a linear classifier in extreme multi-label text classification. ESANN (2020)
Sujay Khandagale, Han Xiao, Rohit Babbar
Bonsai: diverse and shallow trees for extreme multi-label classification. Mach. Learn. 109 (11) (2020)
Erik Schultheis, Mohammadreza Qaraei, Priyanshu Gupta, Rohit Babbar
Unbiased Loss Functions for Extreme Classification With Missing Labels. CoRR (2020)
Rohit Babbar, Bernhard Schölkopf
Data scarcity, robustness and extreme multi-label classification. Mach. Learn. 108 (8-9) (2019)
Sujay Khandagale, Han Xiao, Rohit Babbar
Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification. CoRR (2019)
Sujay Khandagale, Rohit Babbar
A Simple and Effective Scheme for Data Pre-processing in Extreme Classification. ESANN (2019)
Rohit Babbar, Bernhard Schölkopf
Adversarial Extreme Multi-label Classification. CoRR (2018)
Rohit Babbar, Bernhard Schölkopf
DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification. WSDM (2017)
Rohit Babbar, Bernhard Schölkopf
DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification. CoRR (2016)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard
Learning Taxonomy Adaptation in Large-scale Classification. J. Mach. Learn. Res. 17 (2016)
Rohit Babbar, Krikamol Muandet, Bernhard Schölkopf
TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification. SDM (2016)
Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini
Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data. IDA (2015)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
Re-ranking approach to classification in large-scale power-law distributed category systems. SIGIR (2014)
Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
On power law distributions in large-scale taxonomies. SIGKDD Explor. 16 (1) (2014)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
On Flat versus Hierarchical Classification in Large-Scale Taxonomies. NIPS (2013)
Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Éric Gaussier, Massih-Reza Amini
Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law. ESWC (Satellite Events) (2013)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification. ICONIP (1) (2013)
Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard
Adaptive Classifier Selection in Large-Scale Hierarchical Classification. ICONIP (3) (2012)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard
On empirical tradeoffs in large scale hierarchical classification. CIKM (2012)
Rohit Babbar, Nidhi Singh
Clustering based approach to learning regular expressions over large alphabet for noisy unstructured text. AND (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rohit Babbar