Raghav Somani

Publication Activity (10 Years)

Years Active: 2017-2022
Publications (10 Years): 17

Top Topics

Linear Regression

Robust Statistics

Top Venues

Publications

Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi
Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR (2022)
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
Defense against backdoor attacks via robust covariance estimation. ICML (2021)
Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. CoRR (2021)
Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. NeurIPS (2021)
Sewoong Oh, Soumik Pal, Raghav Somani, Raghav Tripathi
Gradient flows on graphons: existence, convergence, continuity equations. CoRR (2021)
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR (2021)
Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh
Meta-learning for mixed linear regression. CoRR (2020)
Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh
Meta-learning for Mixed Linear Regression. ICML (2020)
Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh
Robust Meta-learning for Mixed Linear Regression with Small Batches. NeurIPS (2020)
Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh
Robust Meta-learning for Mixed Linear Regression with Small Batches. CoRR (2020)
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi
Soft Threshold Weight Reparameterization for Learnable Sparsity. CoRR (2020)
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi
Soft Threshold Weight Reparameterization for Learnable Sparsity. ICML (2020)
Abhishek Panigrahi, Raghav Somani, Navin Goyal, Praneeth Netrapalli
Non-Gaussianity of Stochastic Gradient Noise. CoRR (2019)
Gaurush Hiranandani, Raghav Somani, Oluwasanmi Koyejo, Sreangsu Acharyya
Clustered Monotone Transforms for Rating Factorization. WSDM (2019)
Raghav Somani, Chirag Gupta, Prateek Jain, Praneeth Netrapalli
Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds. NeurIPS (2018)
Gaurush Hiranandani, Raghav Somani, Oluwasanmi Koyejo, Sreangsu Acharyya
Clustered Monotone Transforms for Rating Factorization. CoRR (2018)
Arabin Kumar Dey, Raghav Somani, Sreangsu Acharyya
A case study of Empirical Bayes in User-Movie Recommendation system. CoRR (2017)