2022

• CascadeXML : Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-Label Classification (pdf , code),
  Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis and Rohit Babbar
  36th Conference on Neural Information Processing Systems, NeurIPS, 2022

• On Missing Labels, Long tails and propensities in Extreme Multi-label Classification
  Erik Schultheis, Marek Wydmuch, Rohit Babbar, and Krzysztof Dembczyński
  28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022

• Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization, 2021, (arxiv pre-print)
  Erik Schultheis, Rohit Babbar
  ECML & Machine Learning Journal Track, ECML-MLJ, 2022

2021

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

      Erik Schultheis, Mohammadreza Qaraei, Priyanshu Gupta, Rohit Babbar

      30th , ACM International World Wide Web Conference, The WebConf (WWW) 2021

• Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading

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

      20th IEEE International Conference on Computer Communications, Infocom 2020

• Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification pdf Code Rust implementation by Tom Dong

      Sujay Khandagale, Han Xiao, Rohit Babbar

      Machine Learning Journal 2020

2019

• Data Scarcity, Robustness and Extreme Multi-label Classification pdf Code

      Rohit Babbar and  Bernhard Schölkopf

     Machine Learning Journal and European Conference on Machine Learning 2019, Wurzburg, Germany

    2018

• Adversarial Extreme Multi-label Classification pdf

 Rohit Babbar and  Bernhard Schölkopf

• Prediction of glucose tolerance without an oral glucose tolerance test

Rohit Babbar, Martin Heni, Andreas Peter, Martin Hrabě de Angelis, Hans-Ulrich Häring, Andreas Fritsche, Hubert Preissl, Bernhard Schölkopf, Róbert Wagner

Frontiers in Endocrinology

    2017

• DiSMEC : Distributed Sparse Machines for Extreme Multi-label Classification, pdf Code

Rohit Babbar and  Bernhard Schölkopf

ACM International Conference on Web Search and Data Mining (WSDM) 2017, Cambridge;

Also accepted for NIPS 2016 Extreme Classification Workshop

   2016

• Learning Taxonomy Adaptation in Large-scale Classification

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

Journal of Machine Learning Research , (JMLR 2016)

• TerseSVM : A scalable approach for learning compact models in Large-scale classification

Rohit Babbar, Krikamol Muandet, and  Bernhard Schölkopf

SIAM International Conference on Data Mining (SDM 2016), Miami

   2015

• Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data 

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

International Symposium on Intelligent Data Analysis, (IDA 2015),  Saint-Etienne, France

   2014

• Re-ranking Approach to Classification in Large-scale Power-law Distributed Category Systems, pdf

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

ACM SIGIR Conference , (SIGIR 2014), Gold Coast, Australia, 

• On Power Law Distributions in Large-scale Taxonomies", pdf

Rohit Babbar, Cornelia Metzig,  Ioannis Partalas, Eric Gaussier and Massih-reza Amini

SIGKDD Explorations Journal, Special Issue on Big Data

  2013

• On Flat versus Hierarchical Classification in Large-Scale Taxonomies", pdf  

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini

Neural Information Processing Systems, (NIPS 2013), Lake Tahoe, Neveda, USA

• Maximum-margin Framework for Training Data Synchronization in Large-scale Hierarchical Classification, pdf, 

Rohit Babbar, Ioannis Partalas, Eric Gaussier and Massih-reza Amini 

Intl. Conference on Neural Information Processing, (ICONIP 2013), Daegu, Korea

• Comparative Classifier Evaluation for Web-scale Taxonomies using Power Law, 

Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Eric Gaussier and Massih-reza Amini

European Semantic Web Conference (ESWC 2013), Montpiller, France.

   2012

• On Empirical Tradeoffs in Large Scale Hierarchical Classification, 

Rohit Babbar, Ioannis Partalas, Eric Gaussier, Cecile Amblard

ACM Intl. Conference on Information and Knowledge Management, (CIKM 2012), Maui, Hawaii.

• Adaptive Classifier Selection in Large-scale Hierarchical Classification, 

Ioannis Partalas, Rohit Babbar, Eric Gaussier, Cecile Amblard

Intl. Conference on Neural Information Processing, (ICONIP 2012), Doha, Qatar.