Rohit Babbar - RankMe

64 papers A* 14A 3B 4Journal 30Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language Models. CoRR Jinbin Zhang, Nasib Ullah, Erik Schultheis, Rohit Babbar
2025	A*	`conf`	ELMO : Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces. ICML Jinbin Zhang, Nasib Ullah, Erik Schultheis, Rohit Babbar
2025	J	`jnl`	ELMO: Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces. CoRR Jinbin Zhang, Nasib Ullah, Erik Schultheis, Rohit Babbar
2025	—	`conf`	How Well Calibrated are Extreme Multi-label Classifiers? An Empirical Analysis. KDD (1) Nasib Ullah, Erik Schultheis, Jinbin Zhang, Rohit Babbar
2025	B	`conf`	Large Language Model as a Teacher for Zero-shot Tagging at Extreme Scales. COLING Jinbin Zhang, Nasib Ullah, Rohit Babbar
2025	J	`jnl`	Unbiased Loss Functions for Multilabel Classification with Missing Labels. Trans. Mach. Learn. Res. Erik Schultheis, Rohit Babbar
2025	A*	`conf`	UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification. WWW Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Amit Singh, Cho-Jui Hsieh, Rohit Babbar
2024	A*	`conf`	A General Online Algorithm for Optimizing Complex Performance Metrics. ICML Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis, Rohit Babbar, Krzysztof Dembczynski
2024	J	`jnl`	A General Online Algorithm for Optimizing Complex Performance Metrics. CoRR Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis, Rohit Babbar, Krzysztof Dembczynski
2024	A*	`conf`	Consistent algorithms for multi-label classification with macro-at-k metrics. ICLR Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski
2024	J	`jnl`	Consistent algorithms for multi-label classification with macro-at-k metrics. CoRR Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski
2024	A*	`conf`	Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features. KDD Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
2024	J	`jnl`	Labels in Extremes: How Well Calibrated are Extreme Multi-label Classifiers? CoRR Nasib Ullah, Erik Schultheis, Jinbin Zhang, Rohit Babbar
2024	J	`jnl`	Learning label-label correlations in Extreme Multi-label Classification via Label Features. CoRR Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
2024	J	`jnl`	Meta-classifier free negative sampling for extreme multilabel classification. Mach. Learn. Mohammadreza Qaraei, Rohit Babbar
2024	J	`jnl`	Navigating Extremes: Dynamic Sparsity in Large Output Space. CoRR Nasib Ullah, Erik Schultheis, Mike Lasby, Yani Ioannou, Rohit Babbar
2024	A*	`conf`	Navigating Extremes: Dynamic Sparsity in Large Output Spaces. NeurIPS Nasibullah Nasibullah, Erik Schultheis, Mike Lasby, Yani Ioannou, Rohit Babbar
2024	J	`jnl`	UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification. CoRR Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Cho-Jui Hsieh, Rohit Babbar
2024	J	`jnl`	Zero-Shot Learning Over Large Output Spaces : Utilizing Indirect Knowledge Extraction from Large Language Models. CoRR Jinbin Zhang, Nasib Ullah, Rohit Babbar
2023	A*	`conf`	Generalized test utilities for long-tail performance in extreme multi-label classification. NeurIPS Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski
2023	J	`jnl`	Generalized test utilities for long-tail performance in extreme multi-label classification. CoRR Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski
2023	A*	`conf`	InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification. SIGIR Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta, Akash Palrecha, Rohit Babbar
2023	J	`jnl`	Towards Memory-Efficient Training for Extremely Large Output Spaces - Learning with 500k Labels on a Single Commodity GPU. CoRR Erik Schultheis, Rohit Babbar
2023	—	`conf`	Towards Memory-Efficient Training for Extremely Large Output Spaces - Learning with 670k Labels on a Single Commodity GPU. ECML/PKDD (3) Erik Schultheis, Rohit Babbar
2023	—	`conf`	Using ECCO-BERT and the Historical Thesaurus of English to Explore Concepts and Agency in Historical Writing Interpreting the Eighteenth-century Luxury Debate. DH 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
2022	J	`jnl`	Adversarial examples for extreme multilabel text classification. Mach. Learn. Mohammadreza Qaraei, Rohit Babbar
2022	A*	`conf`	CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification. NeurIPS Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar
2022	J	`jnl`	CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification. CoRR Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar
2022	—	`conf`	Detecting Sequential Genre Change in Eighteenth-Century Texts. CHR Jinbin Zhang, Yann Ciarán Ryan, Iiro Rastas, Filip Ginter, Mikko Tolonen, Rohit Babbar
2022	—	`conf`	Explainable Publication Year Prediction of Eighteenth Century Texts with the BERT Model. LChange@ACL Iiro Rastas, Yann Ciarán Ryan, Iiro Tiihonen, Mohammadreza Qaraei, Liina Repo, Rohit Babbar, Eetu Mäkelä, Mikko Tolonen, Filip Ginter
2022	—	`ch.`	Extreme Multicore Classification. Mach. Learn. under Resour. Constraints Vol. 1 (1) Erik Schultheis, Rohit Babbar
2022	A*	`conf`	On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification. KDD Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski
2022	J	`jnl`	On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification. CoRR Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski
2022	J	`jnl`	Speeding-up one-versus-all training for extreme classification via mean-separating initialization. Mach. Learn. Erik Schultheis, Rohit Babbar
2021	J	`jnl`	Adversarial Examples for Extreme Multilabel Text Classification. CoRR Mohammadreza Qaraei, Rohit Babbar
2021	A*	`conf`	Convex Surrogates for Unbiased Loss Functions in Extreme Classification With Missing Labels. WWW Mohammadreza Qaraei, Erik Schultheis, Priyanshu Gupta, Rohit Babbar
2021	J	`jnl`	Embedding Convolutions for Short Text Extreme Classification with Millions of Labels. CoRR Siddhant Kharbanda, Atmadeep Banerjee, Akash Palrecha, Rohit Babbar
2021	A*	`conf`	Propensity-scored Probabilistic Label Trees. SIGIR Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczynski
2021	J	`jnl`	Propensity-scored Probabilistic Label Trees. CoRR Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczynski
2021	J	`jnl`	Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization. CoRR Erik Schultheis, Rohit Babbar
2021	J	`jnl`	Unbiased Loss Functions for Multilabel Classification with Missing Labels. CoRR Erik Schultheis, Rohit Babbar
2020	J	`jnl`	Bonsai: diverse and shallow trees for extreme multi-label classification. Mach. Learn. Sujay Khandagale, Han Xiao, Rohit Babbar
2020	A*	`conf`	Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading. INFOCOM Thaha Mohammed, Carlee Joe-Wong, Rohit Babbar, Mario Di Francesco
2020	—	`conf`	Neural Architecture Search for Extreme Multi-label Text Classification. ICONIP (3) Loïc Pauletto, Massih-Reza Amini, Rohit Babbar, Nicolas Winckler
2020	J	`jnl`	Unbiased Loss Functions for Extreme Classification With Missing Labels. CoRR Erik Schultheis, Mohammadreza Qaraei, Priyanshu Gupta, Rohit Babbar
2020	B	`conf`	Why state-of-the-art deep learning barely works as good as a linear classifier in extreme multi-label text classification. ESANN Mohammadreza Qaraei, Sujay Khandagale, Rohit Babbar
2019	B	`conf`	A Simple and Effective Scheme for Data Pre-processing in Extreme Classification. ESANN Sujay Khandagale, Rohit Babbar
2019	J	`jnl`	Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification. CoRR Sujay Khandagale, Han Xiao, Rohit Babbar
2019	J	`jnl`	Data scarcity, robustness and extreme multi-label classification. Mach. Learn. Rohit Babbar, Bernhard Schölkopf
2018	J	`jnl`	Adversarial Extreme Multi-label Classification. CoRR Rohit Babbar, Bernhard Schölkopf
2017	A	`conf`	DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification. WSDM Rohit Babbar, Bernhard Schölkopf
2016	J	`jnl`	DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification. CoRR Rohit Babbar, Bernhard Schölkopf
2016	J	`jnl`	Learning Taxonomy Adaptation in Large-scale Classification. J. Mach. Learn. Res. Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard
2016	A	`conf`	TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification. SDM Rohit Babbar, Krikamol Muandet, Bernhard Schölkopf
2015	B	`conf`	Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data. IDA Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini
2014	—	`—`	Machine Learning Strategies for Large-scale Taxonomies. (Strategies d'apprentissage pour la classification dans les grandes taxonomies). Rohit Babbar
2014	J	`jnl`	On power law distributions in large-scale taxonomies. SIGKDD Explor. Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2014	A*	`conf`	Re-ranking approach to classification in large-scale power-law distributed category systems. SIGIR Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2013	—	`conf`	Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law. ESWC (Satellite Events) Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Éric Gaussier, Massih-Reza Amini
2013	—	`conf`	Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification. ICONIP (1) Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2013	—	`conf`	On Flat versus Hierarchical Classification in Large-Scale Taxonomies. NIPS Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2012	—	`conf`	Adaptive Classifier Selection in Large-Scale Hierarchical Classification. ICONIP (3) Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard
2012	A	`conf`	On empirical tradeoffs in large scale hierarchical classification. CIKM Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard
2010	—	`conf`	Clustering based approach to learning regular expressions over large alphabet for noisy unstructured text. AND Rohit Babbar, Nidhi Singh