Rohit Babbar

Aalto SCI Computer Science Konemiehentie 2

Research activity per year

If you made any changes in Pure these will be visible here soon.

Artistic and research interests

I am an Assistant Professor at the department of Computer Science, Aalto University in Finland. Along with my research group, we work on problems in large scale machine learning particularly encountered in extreme classification with large output spaces, and robustness

Keywords

large scale learning
extreme multi-label classification
deep learning
sequential data
robustness

Fingerprint

Dive into the research topics where Rohit Babbar is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

15 Conference contribution
5 Article
2 Working paper

Convex Surrogates for Unbiased Loss Functions in Extreme Classification With Missing Labels
Mohammadnia Qaraei, M., Schultheis, E., Gupta, P. & Babbar, R., 19 Apr 2021, WWW '21: Proceedings of the Web Conference 2021. ACM, p. 3711-3720 10 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Open Access
File
13 Downloads (Pure)
Propensity-scored Probabilistic Label Trees
Wydmuch, M., Jasinska-Kobus, K., Babbar, R. & Dembczynski, K., 11 Jul 2021, SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, p. 2252–2256 5 p. 3463084
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification
Khandagale, S., Xiao, H. & Babbar, R., 23 Aug 2020, In: Machine Learning.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
43 Downloads (Pure)
Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading
Mohammed, T., Joe-Wong, C., Babbar, R. & Francesco, M. D., Jul 2020, INFOCOM 2020 - IEEE Conference on Computer Communications. IEEE, p. 854-863 10 p. 9155237. (Proceedings - IEEE INFOCOM; vol. 2020-July).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Open Access
File
13 Citations (Scopus)

323 Downloads (Pure)
Neural Architecture Search for Extreme Multi-label Text Classification
Pauletto, L., Amini, M-R., Babbar, R. & Winckler, N., 2020, International Conference on Neural Information Processing: ICONIP 2020: Neural Information Processing . p. 282-293 12 p. (Lecture Notes in Computer Science; vol. 12534).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Open Access

1 Organization of a workshop, panel, session or tutorial
1 Participant of a conference, workshop, session or tutorial

Dagstuhl Seminar
Rohit Babbar (Member)
15 Jul 2018 → 20 Jul 2018
Activity: Participating in or organising an event types › Participant of a conference, workshop, session or tutorial
Tutorial on Extreme Classification for Information Retrieval
Rohit Babbar (Member)
26 Apr 2018
Activity: Participating in or organising an event types › Organization of a workshop, panel, session or tutorial

Rohit Babbar

Personal profile

Artistic and research interests

Keywords

Fingerprint

Research output

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

Propensity-scored Probabilistic Label Trees

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

Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading

Neural Architecture Search for Extreme Multi-label Text Classification

Activities

Dagstuhl Seminar

Tutorial on Extreme Classification for Information Retrieval