Thakurta, Abhradeep

19 publications

AISTATS 2024 Private Learning with Public Features Walid Krichene, Nicolas E Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang

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

COLT 2023 Differentially Private and Lazy Online Convex Optimization Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Thakurta

COLT 2023 Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay

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

COLT 2022 Private Matrix Approximation and Geometry of Unitary Orbits Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, Nisheeth K. Vishnoi

ICML 2022 Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Thomas Steinke, Vinith M Suriyakumar, Om Thakkar, Abhradeep Thakurta

AISTATS 2021 Evading the Curse of Dimensionality in Unconstrained Private GLMs Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta

COLT 2021 (Nearly) Dimension Independent Private ERM with AdaGrad Rates\{via Publicly Estimated Subspaces Peter Kairouz, Monica Ribero Diaz, Keith Rush, Abhradeep Thakurta

ICML 2021 Practical and Private (Deep) Learning Without Sampling or Shuffling Peter Kairouz, Brendan Mcmahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu

ICML 2021 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang

AAAI 2021 Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson

JMLR 2020 Practical Locally Private Heavy Hitters Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Thakurta

ICML 2018 Differentially Private Matrix Completion Revisited Prateek Jain, Om Dipakbhai Thakkar, Abhradeep Thakurta

UAI 2015 (Nearly) Optimal Differentially Private Stochastic Multi-Arm Bandits Nikita Mishra, Abhradeep Thakurta

COLT 2013 Differentially Private Feature Selection via Stability Arguments, and the Robustness of the Lasso Abhradeep Thakurta, Adam D. Smith

ICML 2013 Differentially Private Learning with Kernels Prateek Jain, Abhradeep Thakurta

COLT 2012 Differentially Private Online Learning Prateek Jain, Pravesh Kothari, Abhradeep Thakurta

COLT 2012 Private Convex Empirical Risk Minimization and High-Dimensional Regression Daniel Kifer, Adam Smith, Abhradeep Thakurta