Thakkar, Om

11 publications

ICLR 2023 Measuring Forgetting of Memorized Training Examples Matthew Jagielski, Om Thakkar, Florian Tramer, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang

ICML 2023 Why Is Public Pretraining Necessary for Private Model Training? Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang

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

AAAI 2022 The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar

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

NeurIPS 2021 Differentially Private Learning with Adaptive Clipping Galen Andrew, Om Thakkar, Brendan McMahan, Swaroop Ramaswamy

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

NeurIPS 2021 Revealing and Protecting Labels in Distributed Training Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays

AISTATS 2020 Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis Ryan Rogers, Aaron Roth, Adam Smith, Nathan Srebro, Om Thakkar, Blake Woodworth

NeurIPS 2020 Privacy Amplification via Random Check-Ins Borja Balle, Peter Kairouz, Brendan McMahan, Om Thakkar, Abhradeep Guha Thakurta

NeurIPS 2018 Model-Agnostic Private Learning Raef Bassily, Om Thakkar, Abhradeep Guha Thakurta