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ORCIDRaghav Somani
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Conference and Workshop Papers
- 2021
[c7]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
Defense against backdoor attacks via robust covariance estimation. ICML 2021: 4129-4139- [c6]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: 23900-23913 - 2020
- [c5]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for Mixed Linear Regression. ICML 2020: 5394-5404 - [c4]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. ICML 2020: 5544-5555 - [c3]Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh:
Robust Meta-learning for Mixed Linear Regression with Small Batches. NeurIPS 2020 - 2019
- [c2]Gaurush Hiranandani, Raghav Somani
, Oluwasanmi Koyejo, Sreangsu Acharyya:
Clustered Monotone Transforms for Rating Factorization. WSDM 2019: 132-140 - 2018
- [c1]Raghav Somani, Chirag Gupta, Prateek Jain, Praneeth Netrapalli:
Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds. NeurIPS 2018: 10837-10847
Informal and Other Publications
- 2022
- [i10]Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi:
Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR abs/2210.00422 (2022) - 2021
- [i9]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR abs/2104.11315 (2021) - [i8]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 abs/2106.01487 (2021) - [i7]Sewoong Oh, Soumik Pal, Raghav Somani, Raghav Tripathi:
Gradient flows on graphons: existence, convergence, continuity equations. CoRR abs/2111.09459 (2021) - 2020
- [i6]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. CoRR abs/2002.03231 (2020) - [i5]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for mixed linear regression. CoRR abs/2002.08936 (2020) - [i4]Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh:
Robust Meta-learning for Mixed Linear Regression with Small Batches. CoRR abs/2006.09702 (2020) - 2019
- [i3]Abhishek Panigrahi, Raghav Somani, Navin Goyal, Praneeth Netrapalli:
Non-Gaussianity of Stochastic Gradient Noise. CoRR abs/1910.09626 (2019) - 2018
- [i2]Gaurush Hiranandani, Raghav Somani, Oluwasanmi Koyejo, Sreangsu Acharyya:
Clustered Monotone Transforms for Rating Factorization. CoRR abs/1811.00159 (2018) - 2017
- [i1]Arabin Kumar Dey, Raghav Somani, Sreangsu Acharyya:
A case study of Empirical Bayes in User-Movie Recommendation system. CoRR abs/1707.02294 (2017)
Coauthor Index
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