| Attack of the tails: Yes, you really can backdoor federated learning H Wang, K Sreenivasan, S Rajput, H Vishwakarma, S Agarwal, J Sohn, ... Advances in Neural Information Processing Systems 33, 2020 | 961 | 2020 |
| Optimal lottery tickets via subsetsum: Logarithmic over-parameterization is sufficient A Pensia, S Rajput, A Nagle, H Vishwakarma, D Papailiopoulos Advances in Neural Information Processing Systems 33, 2020 | 138 | 2020 |
| Quantum embedding of knowledge for reasoning D Garg, S Ikbal, SK Srivastava, H Vishwakarma, H Karanam, ... Advances in Neural Information Processing Systems 32, 2019 | 76 | 2019 |
| Universalizing weak supervision C Shin, W Li, H Vishwakarma, N Roberts, F Sala International Conference on Learning Representations (ICLR) 2022, 2021 | 49 | 2021 |
| An end-to-end machine learning pipeline that ensures fairness policies S Shaikh, H Vishwakarma, S Mehta, KR Varshney, KN Ramamurthy, ... Bloomberg Data for Good Exchange, 2017 | 25 | 2017 |
| Promises and pitfalls of threshold-based auto-labeling H Vishwakarma, H Lin, F Sala, R Korlakai Vinayak Advances in Neural Information Processing Systems 36, 2023 | 21 | 2023 |
| Taming False Positives in Out-of-Distribution Detection with Human Feedback H Vishwakarma, H Lin, RK Vinayak arXiv preprint arXiv:2404.16954, 2024 | 15* | 2024 |
| Scriptorium WS: A Code Generation Assistant for Weak Supervision TH Huang, C Cao, S Schoenberg, H Vishwakarma, N Roberts, F Sala DL4C Workshop, ICLR 2023, 2023 | 11 | 2023 |
| Know Thy Neighbors, and More! Studying the Role of Context in Entity Recommendation S Bhatia, H Vishwakarma Proceedings of the 29th ACM Conference on Hypertext and Social Media, 2018 | 11 | 2018 |
| Lifting Weak Supervision To Structured Prediction H Vishwakarma, F Sala Advances in Neural Information Processing Systems, 35, 2022 | 9 | 2022 |
| Prune'n Predict: Optimizing LLM Decision-making with Conformal Prediction H Vishwakarma, A Mishler, T Cook, N Dalmasso, N Raman, S Ganesh Forty-second International Conference on Machine Learning, 2025 | 8* | 2025 |
| Pearls from Pebbles: Improved Confidence Functions for Auto-labeling H Vishwakarma, SJ Tay, SSS Namburi, F Sala, RK Vinayak Advances in Neural Information Processing Systems 37, 2024 | 7 | 2024 |
| Cogniculture: Towards a better human-machine co-evolution RR Pimplikar, K Mukherjee, G Parija, H Vishwakarma, R Narayanam, ... arXiv preprint arXiv:1712.03724, 2017 | 7 | 2017 |
| OTTER: Effortless Label Distribution Adaptation of Zero-shot Models C Shin, J Zhao, S Cromp, H Vishwakarma, F Sala Advances in Neural Information Processing Systems 37, 44064-44101, 2024 | 4 | 2024 |
| Train'n Trade: Foundations of Parameter Markets TH Huang, H Vishwakarma, F Sala Advances in Neural Information Processing Systems 36, 2023 | 4 | 2023 |
| Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL H Vishwakarma, Y Chen, SSSN GNVV, SJ Tay, RK Vinayak, F Sala Forty-second International Conference on Machine Learning, 2025 | 3* | 2025 |
| Time To Impeach LLM-as-a-Judge: Programs are the Future of Evaluation TH Huang, H Vishwakarma, F Sala arXiv preprint arXiv:2506.10403, 2025 | 2 | 2025 |
| Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection D Yamada, H Vishwakarma, RK Vinayak arXiv preprint arXiv:2505.02299, 2025 | 1 | 2025 |
| Adaptive Out-of-Distribution Detection with Human-in-the-Loop H Lin, H Vishwakarma, RK Vinayak ICML 2022 Workshop on Human-Machine Collaboration and Teaming, Baltimore, 2022 | 1 | 2022 |
| Automating Benchmark Design A Dsouza, H Vishwakarma, Z Qi, J Bauer, D Pham, T Walshe, A Parchami, ... arXiv preprint arXiv:2510.25039, 2025 | | 2025 |
Frederic SalaAssistant Professor, University of WisconsinVerified email at cs.wisc.edu
