Rohit Babbar

Assistant Professor

Research outputs

  1. 2019
  2. Published

    Data scarcity, robustness and extreme multi-label classification

    Babbar, R. & Schölkopf, B., 15 Sep 2019, In : Machine Learning. 108, 8-9, p. 1329-1351 23 p.

    Research output: Contribution to journalArticleScientificpeer-review

  3. Published

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

    Khandagale, S. & Babbar, R., 26 Apr 2019, ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 67-72

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  4. Published

    Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification

    Khandagale, S., Xiao, H. & Babbar, R., 17 Apr 2019, In : arXiv.org.

    Research output: Contribution to journalArticleScientific

  5. 2018
  6. Published

    Prediction of glucose tolerance without an oral glucose tolerance test

    Babbar, R., Heni, M., Peter, A., de Angelis, M. H., Häring, H. U., Fritsche, A., Preissl, H., Schölkopf, B. & Wagner, R., 19 Mar 2018, In : Frontiers in Endocrinology. 9, MAR, 82.

    Research output: Contribution to journalArticleScientificpeer-review

  7. Published

    Extreme Multi-label Classification for Information Retrieval

    Dembczynski, K. & Babbar, R., 2018, Advances in Information Retrieval: 40th European Conference on IR Research, ECIR 2018, Grenoble, France, March 26-29, 2018, Proceedings. Pasi, G., Piwowarski, B., Azzopardi, L. & Hanbury, A. (eds.). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND: Springer International Publishing AG, Vol. 10772. p. 839-840 2 p. (Lecture Notes in Computer Science).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  8. 2017
  9. Published

    DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification

    Babbar, R. & Schölkopf, B., 2017.

    Research output: Contribution to conferencePaperScientificpeer-review

  10. 2016
  11. Published

    Learning Taxonomy Adaptation in Large-scale Classification

    Babbar, R., Partalas, I., Gaussier, E., Amini, M-R. & Amblard, C., 2016, In : Journal of Machine Learning Research.

    Research output: Contribution to journalArticleScientificpeer-review

  12. Published

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

    Babbar, R., Muandet, K. & Schölkopf, B., 2016.

    Research output: Contribution to conferencePaperScientificpeer-review

  13. 2015
  14. Published

    Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data

    Balikas, G., Partalas, I., Gaussier, E., Babbar, R. & Amini, M-R., 2015.

    Research output: Contribution to conferencePaperScientificpeer-review

  15. 2014
  16. Published

    On Power Law Distributions in Large-scale Taxonomies

    Babbar, R., Partalas, I., Metzig, C., Gaussier, E. & Amini, M-R., 2014, In : SIGKDD Explorations. 16, 1, p. 47-56

    Research output: Contribution to journalArticleScientificpeer-review

ID: 16829878