CS-NET at SemEval-2020 Task 4: Siamese BERT for ComVE. - Soumya Ranjan Dash; Sandeep Routray; Prateek Varshney; Ashutosh Modi (SemEval@COLING, 2020)

(Nearly) Optimal Private Linear Regression for Sub-Gaussian Data via Adaptive Clipping. - Prateek Varshney; Abhradeep Thakurta; Prateek Jain 002 (COLT, 2022)

(Nearly) Optimal Private Linear Regression via Adaptive Clipping. - Prateek Varshney; Abhradeep Thakurta; Prateek Jain 002 (CoRR, 2022)

Private and Efficient Meta-Learning with Low Rank and Sparse Decomposition. - Soumyabrata Pal; Prateek Varshney; Prateek Jain 002; Abhradeep Guha Thakurta; Gagan Madan; Gaurav Aggarwal; Pradeep Shenoy; Gaurav Srivastava 004 (CoRR, 2022)

Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components. - Soumyabrata Pal; Prateek Varshney; Gagan Madan; Prateek Jain 002; Abhradeep Thakurta; Gaurav Aggarwal; Pradeep Shenoy; Gaurav Srivastava 004 (AISTATS, 2024)

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD. - Aniket Das; Dheeraj Nagaraj; Soumyabrata Pal; Arun Sai Suggala; Prateek Varshney (NeurIPS, 2024)

Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization. - Prateek Varshney; Mert Pilanci (CoRR, 2024)