Publications

Machine learning

• 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
  under review (all hail Reviewer 2)
  

Machine learning Information theory

• 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
  

• 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
  

Machine learning Optimization

• 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
  

Blockchains

• 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)

Information theory

• 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

Stochastic approximations

• 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