| Parabel: Partitioned label trees for extreme classification with application to dynamic search advertising Y Prabhu, A Kag, S Harsola, R Agrawal, M Varma Proceedings of the 2018 World Wide Web Conference, 993-1002, 2018 | 267 | 2018 |
| Extreme multi-label learning with label features for warm-start tagging, ranking & recommendation Y Prabhu, A Kag, S Gopinath, K Dahiya, S Harsola, R Agrawal, M Varma Proceedings of the eleventh ACM international conference on web search and …, 2018 | 84 | 2018 |
| Rnns incrementally evolving on an equilibrium manifold: A panacea for vanishing and exploding gradients? A Kag, Z Zhang, V Saligrama International Conference on Learning Representations, 2019 | 67* | 2019 |
| Selective classification via one-sided prediction A Gangrade, A Kag, V Saligrama International Conference on Artificial Intelligence and Statistics, 2179-2187, 2021 | 40 | 2021 |
| Training recurrent neural networks via forward propagation through time A Kag, V Saligrama International Conference on Machine Learning, 5189-5200, 2021 | 34 | 2021 |
| Time adaptive recurrent neural network A Kag, V Saligrama Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 14 | 2021 |
| {BLAS-on-flash}: An Efficient Alternative for Large Scale {ML} Training and Inference? SJ Subramanya, HV Simhadri, S Garg, A Kag, V Balasubramanian 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2019 | 12 | 2019 |
| Efficient edge inference by selective query A Kag, I Fedorov International Conference on Learning Representations, 2023 | 6* | 2023 |
| Online selective classification with limited feedback A Gangrade, A Kag, A Cutkosky, V Saligrama Advances in Neural Information Processing Systems 34, 14529-14541, 2021 | 6 | 2021 |
| Scaffolding a student to instill knowledge A Kag, DAE Acar, A Gangrade, V Saligrama The Eleventh International Conference on Learning Representations, 2022 | 4 | 2022 |
| Condensing cnns with partial differential equations A Kag, V Saligrama Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 4 | 2022 |
| Novel neural architectures & algorithms for efficient inference A Kag Boston University, 2023 | | 2023 |
| Condensing CNNs with partial differential equations V Saligrama, A Kag | | 2022 |
| Hybrid Cloud-Edge Networks for Efficient Inference A Kag, I Fedorov, A Gangrade, P Whatmough, V Saligrama | | 2021 |
| Learning Compact Networks via Adaptive Network Regularization S Sankarapandian, A Kag, R Manzelli, B Kulis | | 2018 |
Venkatesh SaligramaProfessor, Electrical and Computer Engineering, Boston UniversityVerified email at bu.edu
