Generalizing across domains via cross-gradient training S Shankar, V Piratla, S Chakrabarti, S Chaudhuri, P Jyothi, S Sarawagi arXiv preprint arXiv:1804.10745, 2018 | 597 | 2018 |
Efficient domain generalization via common-specific low-rank decomposition V Piratla, P Netrapalli, S Sarawagi International conference on machine learning, 7728-7738, 2020 | 218 | 2020 |
Parallel iterative edit models for local sequence transduction A Awasthi, S Sarawagi, R Goyal, S Ghosh, V Piratla arXiv preprint arXiv:1910.02893, 2019 | 178 | 2019 |
Focus on the common good: Group distributional robustness follows V Piratla, P Netrapalli, S Sarawagi arXiv preprint arXiv:2110.02619, 2021 | 30 | 2021 |
Training for the future: A simple gradient interpolation loss to generalize along time A Nasery, S Thakur, V Piratla, A De, S Sarawagi Advances in Neural Information Processing Systems 34, 19198-19209, 2021 | 26 | 2021 |
An analysis of frame-skipping in reinforcement learning S Kalyanakrishnan, S Aravindan, V Bagdawat, V Bhatt, H Goka, A Gupta, ... arXiv preprint arXiv:2102.03718, 2021 | 22 | 2021 |
Parameter estimation of tuberculosis transmission model using Ensemble Kalman filter across Indian states and union territories P Narula, V Piratla, A Bansal, S Azad, P Lio Infection, Disease & Health 21 (4), 184-191, 2016 | 15 | 2016 |
Historical research using email archives S Hangal, V Piratla, C Manovit, P Chan, G Edwards, MS Lam Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human …, 2015 | 11 | 2015 |
Human-in-the-loop mixup KM Collins, U Bhatt, W Liu, V Piratla, I Sucholutsky, B Love, A Weller Uncertainty in Artificial Intelligence, 454-464, 2023 | 8 | 2023 |
Active assessment of prediction services as accuracy surface over attribute combinations V Piratla, S Chakrabarti, S Sarawagi Advances in Neural Information Processing Systems 34, 23140-23151, 2021 | 5 | 2021 |
Robustness, Evaluation and Adaptation of Machine Learning Models in the Wild V Piratla arXiv preprint arXiv:2303.02781, 2023 | 3 | 2023 |
Topic sensitive attention on generic corpora corrects sense bias in pretrained embeddings V Piratla, S Sarawagi, S Chakrabarti arXiv preprint arXiv:1906.02688, 2019 | 3 | 2019 |
Nlp service apis and models for efficient registration of new clients S Shah, V Piratla, S Chakrabarti, S Sarawagi arXiv preprint arXiv:2010.01526, 2020 | 2 | 2020 |
Autonomous navigation in gps denied indoor environment using rgbd sensor, kinect V Piratla, SB Malode, SK Saini, A Jakhotia, AK Sao, BS Rajpurohit, ... Fourth Symposium on Indoor Flight Issues, 12, 2012 | 2 | 2012 |
Certification of distributional individual fairness M Wicker, V Piratla, A Weller Advances in Neural Information Processing Systems 36, 27670-27681, 2023 | 1 | 2023 |
Use perturbations when learning from explanations J Heo, V Piratla, M Wicker, A Weller Advances in Neural Information Processing Systems 36, 26872-26897, 2023 | 1 | 2023 |
Estimation of concept explanations should be uncertainty aware V Piratla, J Heo, KM Collins, S Singh, A Weller arXiv preprint arXiv:2312.08063, 2023 | 1 | 2023 |
Web-based elicitation of human perception on mixup data KM Collins, U Bhatt, W Liu, V Piratla, B Love, A Weller arXiv preprint arXiv:2211.01202, 2022 | 1 | 2022 |
Robust Learning from Explanations. J Heo, V Piratla, M Wicker, A Weller CoRR, 2023 | | 2023 |
Implicit Training of Energy Model for Structure Prediction S Shankar, V Piratla arXiv preprint arXiv:2211.11649, 2022 | | 2022 |