Raising The Bar For Vertex Cover: Fixed-parameter Tractability Above A Higher Guarantee. - Shivam Garg 001; Geevarghese Philip (SODA, 2016)

A Spectral View of Adversarially Robust Features. - Shivam Garg 001; Vatsal Sharan; Brian Hu Zhang; Gregory Valiant (NeurIPS, 2018)

Sample Amplification: Increasing Dataset Size even when Learning is Impossible. - Brian Axelrod; Shivam Garg 001; Vatsal Sharan; Gregory Valiant (ICML, 2020)

A Model for Ant Trail Formation and its Convergence Properties. - Moses Charikar; Shivam Garg 001; Deborah M. Gordon; Kirankumar Shiragur (CoRR, 2020)

Reward Identification in Inverse Reinforcement Learning. - Kuno Kim; Shivam Garg 001; Kirankumar Shiragur; Stefano Ermon (ICML, 2021)

A Model for Ant Trail Formation and its Convergence Properties (Extended Abstract). - Moses Charikar; Shivam Garg 001; Deborah M. Gordon; Kirankumar Shiragur (ITCS, 2021)

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. - Shivam Garg 001; Dimitris Tsipras; Percy Liang; Gregory Valiant (NeurIPS, 2022)

On the Statistical Complexity of Sample Amplification. - Brian Axelrod; Shivam Garg 001; Yanjun Han; Vatsal Sharan; Gregory Valiant (CoRR, 2022)

Testing with Non-identically Distributed Samples. - Shivam Garg 001; Chirag Pabbaraju; Kirankumar Shiragur; Gregory Valiant (CoRR, 2023)

Discovering Data Structures: Nearest Neighbor Search and Beyond. - Omar Salemohamed; Laurent Charlin; Shivam Garg 001; Vatsal Sharan; Gregory Valiant (CoRR, 2024)