Praneeth Netrapalli

Praneeth Netrapalli

My research interests are broadly in designing reliable and robust machine learning (ML) algorithms, representation learning, black-box optimization, time series modeling, quantum optimization and minimax/game theoretic optimization. I am also extremely interested in applying ML techniques to help solve problems from Sciences as well as enable positive social outcomes.

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Near Optimal Heteroscedastic Regression with Symbiotic Learning
Aniket Das
Dheeraj Baby
Dheeraj Nagaraj
Praneeth Netrapalli
Conference on Learning Theory (COLT) (2023)
Multi User Reinforcement Learning with Low Rank Rewards
Naman Agarwal
Prateek Jain
Suhas Kowshik
Dheeraj Nagaraj
Praneeth Netrapalli
ICML (2023)
LEARNING AN INVERTIBLE OUTPUT MAPPING CAN MITIGATE SIMPLICITY BIAS IN NEURAL NETWORKS
Anshul Nasery
Praneeth Netrapalli
Prateek Jain
Sravanti Addepalli
Will be submitted to ICLR 2023 (2023) (to appear)
Minimax optimization with Smooth Algorithmic Adversaries
Chi Jin
Lillian Ratliff
Praneeth Netrapalli
Tanner Fiez
International Conference on Learning Representations (ICLR) 2022
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
Dheeraj Nagaraj
Naman Agarwal
Praneeth Netrapalli
Prateek Jain
Syomantak Chaudhari
2022
Sample Efficient Linear Meta-Learning
Kiran Koshy Thekumparampil
Praneeth Netrapalli
Prateek Jain
Sewoong Oh
(2021)
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems
Dheeraj Nagaraj
Praneeth Netrapalli
Prateek Jain
Suhas Kowshik
(2021)
Streaming Linear System Identification with Reverse Experience Replay
Dheeraj Nagaraj
Praneeth Netrapalli
Prateek Jain
Suhas Kowshik
(2021)
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