Harikrishna Narasimhan
I am a Senior Research Scientist at Google Research in Mountain View, USA. Prior to joining Google, I was a post-doctoral researcher at Harvard University. I completed my PhD from the Indian Institute of Science, Bangalore. My research interests broadly lie in the areas of machine learning and learning theory, with focus on complex evaluation metrics, constrained optimization and algorithmic fairness.
Please see my personal web page for my full list of publications.
Research Areas
Authored Publications
Sort By
Google
Language Model Cascades: Token-Level Uncertainty And Beyond
Neha Gupta
Aditya Menon
International Conference on Learning Representations (2024)
Post-hoc estimators for learning to defer to an expert
Aditya Krishna Menon
Advances in Neural Information Processing Systems (2022)
Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar
Andy Cotter
Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
Optimal Auctions through Deep Learning
Paul Duetting
Zhe Feng
David C. Parkes
Sai Srivatsa Ravindranath
Communications of the ACM, 64 (Issue 8) (2021), pp. 109-116
Optimizing Blackbox Metrics with Iterative Example Weighting
Gaurush Hiranandani
Jatin Mathur
Mahdi Milani Fard
Sanmi Koyejo
Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
Optimizing Black-box Metrics with Adaptive Surrogates
Qijia Jiang
Olaoluwa Adigun
Mahdi Milani Fard
Maya R. Gupta
Proceedings of the 37th International Conference on Machine Learning (ICML 2020)
Pairwise Fairness for Ranking and Regression
Andy Cotter
Maya Gupta
33rd AAAI Conference on Artificial Intelligence (2020)
