| 2024 | COLT | Second Order Methods for Bandit Optimization and Control. | Arun Suggala, Y. Jennifer Sun, Praneeth Netrapalli, Elad Hazan |
| 2024 | ICML | Tandem Transformers for Inference Efficient LLMs. | Aishwarya P. S., Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli |
| 2024 | ICPR | All Mistakes are not Equal: Comprehensive Hierarchy Aware Multilabel Predictions (CHAMP). | Ashwin Vaswani, Yashas Samaga, Gaurav Aggarwal, Praneeth Netrapalli, Narayan G. Hegde |
| 2023 | COLT | Near Optimal Heteroscedastic Regression with Symbiotic Learning. | Aniket Das, Dheeraj M. Nagaraj, Praneeth Netrapalli, Dheeraj Baby |
| 2023 | ICLR | Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks. | Sravanti Addepalli, Anshul Nasery, Venkatesh Babu Radhakrishnan, Praneeth Netrapalli, Prateek Jain |
| 2023 | ICML | Multi-User Reinforcement Learning with Low Rank Rewards. | Dheeraj Mysore Nagaraj, Suhas S. Kowshik, Naman Agarwal, Praneeth Netrapalli, Prateek Jain |
| 2023 | STOC | Optimistic MLE: A Generic Model-Based Algorithm for Partially Observable Sequential Decision Making. | Qinghua Liu, Praneeth Netrapalli, Csaba Szepesvri, Chi Jin |
| 2022 | ICLR | Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. | Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli |
| 2022 | ICLR | Minimax Optimization with Smooth Algorithmic Adversaries. | Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff |
| 2022 | ICLR | Focus on the Common Good: Group Distributional Robustness Follows. | Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi |
| 2021 | COLT | Efficient Bandit Convex Optimization: Beyond Linear Losses. | Arun Sai Suggala, Pradeep Ravikumar, Praneeth Netrapalli |
| 2021 | ICML | Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization. | Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain |
| 2020 | AAAI | P-SIF: Document Embeddings Using Partition Averaging. | Vivek Gupta, Ankit Saw, Pegah Nokhiz, Praneeth Netrapalli, Piyush Rai, Partha P. Talukdar |
| 2020 | ALT | Leverage Score Sampling for Faster Accelerated Regression and ERM. | Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford |
| 2020 | ALT | Online Non-Convex Learning: Following the Perturbed Leader is Optimal. | Arun Sai Suggala, Praneeth Netrapalli |
| 2020 | ICML | What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization? | Chi Jin, Praneeth Netrapalli, Michael I. Jordan |
| 2020 | ICML | Efficient Domain Generalization via Common-Specific Low-Rank Decomposition. | Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi |
| 2019 | COLT | Open Problem: Do Good Algorithms Necessarily Query Bad Points? | Rong Ge, Prateek Jain, Sham M. Kakade, Rahul Kidambi, Dheeraj M. Nagaraj, Praneeth Netrapalli |
| 2019 | COLT | Making the Last Iterate of SGD Information Theoretically Optimal. | Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli |
| 2019 | ICML | SGD without Replacement: Sharper Rates for General Smooth Convex Functions. | Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli |
| 2018 | COLT | Accelerating Stochastic Gradient Descent for Least Squares Regression. | Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford |
| 2018 | COLT | Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form. | Srinadh Bhojanapalli, Nicolas Boumal, Prateek Jain, Praneeth Netrapalli |
| 2018 | COLT | Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent. | Chi Jin, Praneeth Netrapalli, Michael I. Jordan |
| 2018 | ICLR | On the insufficiency of existing momentum schemes for Stochastic Optimization. | Rahul Kidambi, Praneeth Netrapalli, Prateek Jain, Sham M. Kakade |
| 2018 | ITA | On the Insufficiency of Existing Momentum Schemes for Stochastic Optimization. | Rahul Kidambi, Praneeth Netrapalli, Prateek Jain, Sham M. Kakade |
| 2017 | AISTATS | Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot. | Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli |
| 2017 | COLT | Thresholding Based Outlier Robust PCA. | Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli |
| 2017 | ICML | How to Escape Saddle Points Efficiently. | Chi Jin, Rong Ge, Praneeth Netrapalli, Sham M. Kakade, Michael I. Jordan |
| 2016 | COLT | Information-theoretic thresholds for community detection in sparse networks. | Jess Banks, Cristopher Moore, Joe Neeman, Praneeth Netrapalli |
| 2016 | COLT | Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm. | Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford |
| 2016 | ICML | Faster Eigenvector Computation via Shift-and-Invert Preconditioning. | Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford |
| 2016 | ICML | Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis. | Rong Ge, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford |
| 2015 | COLT | Fast Exact Matrix Completion with Finite Samples. | Prateek Jain, Praneeth Netrapalli |
| 2014 | COLT | Learning Sparsely Used Overcomplete Dictionaries. | Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon |
| 2014 | ISIT | Learning structure of power-law Markov networks. | Abhik Kumar Das, Praneeth Netrapalli, Sujay Sanghavi, Sriram Vishwanath |
| 2013 | ICML | One-Bit Compressed Sensing: Provable Support and Vector Recovery. | Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya V. Nori |
| 2013 | STOC | Low-rank matrix completion using alternating minimization. | Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi |
| 2012 | ISIT | Learning Markov graphs up to edit distance. | Abhik Kumar Das, Praneeth Netrapalli, Sujay Sanghavi, Sriram Vishwanath |
| 2012 | SIGMETRICS | Learning the graph of epidemic cascades. | Praneeth Netrapalli, Sujay Sanghavi |