A case study of Empirical Bayes in User-Movie Recommendation system. - Arabin Kumar Dey; Raghav Somani; Sreangsu Acharyya (CoRR, 2017)

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds. - Raghav Somani; Chirag Gupta; Prateek Jain 002; Praneeth Netrapalli (NeurIPS, 2018)

Clustered Monotone Transforms for Rating Factorization. - Gaurush Hiranandani; Raghav Somani; Oluwasanmi Koyejo; Sreangsu Acharyya (WSDM, 2019)

Non-Gaussianity of Stochastic Gradient Noise. - Abhishek Panigrahi; Raghav Somani; Navin Goyal; Praneeth Netrapalli (CoRR, 2019)

Meta-learning for Mixed Linear Regression. - Weihao Kong; Raghav Somani; Zhao Song 002; Sham M. Kakade; Sewoong Oh (ICML, 2020)

Soft Threshold Weight Reparameterization for Learnable Sparsity. - Aditya Kusupati; Vivek Ramanujan; Raghav Somani; Mitchell Wortsman; Prateek Jain 002; Sham M. Kakade; Ali Farhadi (ICML, 2020)

Robust Meta-learning for Mixed Linear Regression with Small Batches. - Weihao Kong; Raghav Somani; Sham M. Kakade; Sewoong Oh (NeurIPS, 2020)

Defense against backdoor attacks via robust covariance estimation. - Jonathan Hayase; Weihao Kong; Raghav Somani; Sewoong Oh (ICML, 2021)

LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. - Aditya Kusupati; Matthew Wallingford; Vivek Ramanujan; Raghav Somani; Jae Sung Park; Krishna Pillutla; Prateek Jain 002; Sham M. Kakade; Ali Farhadi (NeurIPS, 2021)

SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. - Jonathan Hayase; Weihao Kong; Raghav Somani; Sewoong Oh (CoRR, 2021)

Gradient flows on graphons: existence, convergence, continuity equations. - Sewoong Oh; Soumik Pal; Raghav Somani; Raghav Tripathi (CoRR, 2021)

Stochastic optimization on matrices and a graphon McKean-Vlasov limit. - Zaïd Harchaoui; Sewoong Oh; Soumik Pal; Raghav Somani; Raghavendra Tripathi (CoRR, 2022)

Scaling Limits of Algorithms on Large Matrices - Raghav Somani (2024)