Professorship Babbar R.

Organisational unit: Research group

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

ID: 16559265