Sachdeva, Sushant

11 publications

COLT 2025 PREM: Privately Answering Statistical Queries with Relative Error Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva

ICML 2022 A Convergent and Dimension-Independent Min-Max Optimization Algorithm Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi

NeurIPS 2021 Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization Deeksha Adil, Brian Bullins, Sushant Sachdeva

ICML 2020 Faster Graph Embeddings via Coarsening Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang

NeurIPS 2020 Regularized Linear Autoencoders Recover the Principal Components, Eventually Xuchan Bao, James Lucas, Sushant Sachdeva, Roger B Grosse

NeurIPS 2019 Fast, Provably Convergent IRLS Algorithm for P-Norm Linear Regression Deeksha Adil, Richard Peng, Sushant Sachdeva

AISTATS 2019 Improved Semi-Supervised Learning with Multiple Graphs Krishnamurthy Viswanathan, Sushant Sachdeva, Andrew Tomkins, Sujith Ravi

NeurIPS 2019 Which Algorithmic Choices Matter at Which Batch Sizes? Insights from a Noisy Quadratic Model Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George Dahl, Chris Shallue, Roger B Grosse

COLT 2015 Algorithms for Lipschitz Learning on Graphs Rasmus Kyng, Anup Rao, Sushant Sachdeva, Daniel A. Spielman

NeurIPS 2015 Fast, Provable Algorithms for Isotonic Regression in All L_p-Norms Rasmus Kyng, Anup Rao, Sushant Sachdeva

NeurIPS 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva