Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models with Adway Girish, Alliot Nagle, Marco Bondaschi, Michael C. Gastpar, and Hyeji Kim NeurIPS, 2024
Transformers on Markov Data: Constant Depth Suffices with Nived Rajaraman, Marco Bondaschi, Kannan Ramachandran, and Michael C. Gastpar NeurIPS, 2024
Local to Global: Learning Dynamics and Effect of Initialization for Transformers with Marco Bondaschi, Chanakya Ekbote, Adway Girish, Alliot Nagle, Hyeji Kim, and Michael C. Gastpar NeurIPS, 2024
Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains with Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, and Michael C. Gastpar Mechanistic Interpretability Workshop, ICML 2024 & under review at ICLR 2025
Optimal transport mapping via input convex neural networks with Amirhossein Taghvaei, Jason Lee, and Sewoong Oh ICML, 2020
Learning in Gated Neural Networks with Sreeram Kannan, Sewoong Oh, and Pramod Viswanath AISTATS, 2020
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms with Sewoong Oh, Sreeram Kannan, and Pramod Viswanath ICML, 2019
Learning One-hidden-layer Neural Networks under General Input Distributions with Weihao Gao, Sewoong Oh, and Pramod Viswanath AISTATS, 2019
LASER: Linear Compression in Wireless Distributed Optimization with Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, and Michael C. Gastpar NeurIPS Federated Learning Workshop, 2023 ICML, 2024
CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family with S Ashwin Hebbar, Viraj Nadkarni, Suma Bhat, Sewoong Oh, and Pramod Viswanath ICML, 2023
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes with Mohammad Vahid Jamali, Xiyang Liu, Hessam Mahdavifar, Sewoong Oh, and Pramod Viswanath IEEE Journal on Selected Topics in Information Theory (JSAIT), 2023
TinyTurbo: Efficient Turbo Decoders on Edge with S Ashwin Hebbar, Rajesh K Mishra, Sravan Kumar Ankireddy, Hyeji Kim, and Pramod Viswanath ISIT, 2022
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learning with Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, and Pramod Viswanath ICML, 2021
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding with Mohammad Vahid Jamali, Xiyang Liu, Hessam Mahdavifar, Sewoong Oh, and Pramod Viswanath ISIT, 2021
Barracuda: The Power of l-polling in Proof-of-Stake Blockchains with Ranvir Rana, Jiantao Jao, Sewoong Oh, Giulia Fanti, and Pramod Viswanath ACM MobiHoc, 2019 (Best paper award)
Equivalence of additive-combinatorial linear inequalities for Shannon entropy and differential entropy with Yihong Wu IEEE Transactions on Information Theory, 2018
On additive-combinatorial affine inequalities for Shannon entropy and differential entropy with Yihong Wu IEEE International Symposium on Information Theory (ISIT), 2016
Event-driven stochastic approximation with Vivek S. Borkar and Neeraja Sahasrabudhe Indian Journal of Pure and Applied Mathematics, June 2016, Volume 47, Issue 2, pp 291–299