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I am a graduate student in the Computer Science department at UC Berkeley where I am fortunate to be advised by Peter Bartlett and Anca Dragan. I am interested in problems at the intersection of statistics, optimization and machine learning, in particular on aspects of aligning the objectives of the ML models with those of humans. |
Agnostic learning with unknown utilities
Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, and Jacob Steinhardt,
Innovations in Theoretical Computer Science (ITCS), 2021
Preference learning along multiple criteria: A game-theoretic perspective
Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, and Martin J. Wainwright,
Neural Information Processing Systems (NeurIPS), 2020
ICML workshop on Theoretical Foundations of Reinforcement Learning (oral), 2020
[pdf]
Online learning with dynamics: A minimax perspective
Kush Bhatia, and Karthik Sridharan,
Neural Information Processing Systems (NeurIPS), 2020
[pdf]
Bayesian Robustness: A Nonasymptotic Viewpoint
Kush Bhatia, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett, and Michael I. Jordan,
Under Review, 2019
[pdf]
Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression
Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, and Prateek Jain,
Conference on Learning Theory (COLT), 2019
[pdf]
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction
Yasin Abbasi-Yadkori, Peter L. Bartlett, Kush Bhatia, Nevena Lazic, Csaba Szepesvári, and Gellért Weisz,
International Conference on Machine Learning (ICML), 2019
[pdf]
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, and Martin J. Wainwright,
Journal of Machine Learning Research (JMLR), Jan 2020
Preliminary version at: International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[pdf]
Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation
Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, and Michael I. Jordan,
Neural Information Processing Systems (NeurIPS), 2018
[pdf]
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, and Manik Varma,
Neural Information Processing Systems (NeurIPS), 2018
[pdf]
[Code]
[Short Video]
[Blog]
Establishing Appropriate Trust Via Critical States.
Sandy Huang, Kush Bhatia, Pieter Abbeel, and Anca D. Dragan,
International Conference on Intelligent Robots and Systems (IROS), 2018
[pdf]
Consistent Robust Regression
Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, and Purushottam Kar,
Neural Information Processing Systems (NIPS), 2017
[pdf]
[Short Video]
Robust Regression via Hard Thresholding
Kush Bhatia, Prateek Jain, and Purushottam Kar,
Neural Information Processing Systems (NIPS), 2015
[pdf]
Sparse Local Embeddings for Extreme Multi-label Classification
Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, and Prateek Jain,
Neural Information Processing Systems (NIPS), 2015
[pdf]
[Code]
[Extreme Classification Repository]
Lazy Generic Cuts
Dinesh Khandelwal, Kush Bhatia, Chetan Arora and Parag Singla,
Computer Vision and Image Understanding, 2016
[pdf]