Acharya, Jayadev

41 publications

COLT 2024 The Role of Randomness in Quantum State Certification with Unentangled Measurements Yuhan Liu, Jayadev Acharya

AISTATS 2023 Discrete Distribution Estimation Under User-Level Local Differential Privacy Jayadev Acharya, Yuhan Liu, Ziteng Sun

NeurIPS 2023 Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks Jimmy Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari

AISTATS 2023 Sample Complexity of Distinguishing Cause from Effect Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun

NeurIPS 2023 Unified Lower Bounds for Interactive High-Dimensional Estimation Under Information Constraints Jayadev Acharya, Clément L Canonne, Ziteng Sun, Himanshu Tyagi

NeurIPSW 2022 Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari

NeurIPSW 2022 Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari

COLT 2022 Robust Estimation for Random Graphs Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang

COLT 2022 The Role of Interactivity in Structured Estimation Jayadev Acharya, Clement L. Canonne, Ziteng Sun, Himanshu Tyagi

ALT 2021 Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya, Ziteng Sun, Huanyu Zhang

NeurIPS 2021 Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition Jayadev Acharya, Clement Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi

ALT 2021 Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun

NeurIPS 2021 Information-Constrained Optimization: Can Adaptive Processing of Gradients Help? Jayadev Acharya, Clement Canonne, Prathamesh Mayekar, Himanshu Tyagi

NeurIPS 2021 Optimal Rates for Nonparametric Density Estimation Under Communication Constraints Jayadev Acharya, Clement Canonne, Aditya Vikram Singh, Himanshu Tyagi

ICML 2021 Principal Bit Analysis: Autoencoding with Schur-Concave Loss Sourbh Bhadane, Aaron B Wagner, Jayadev Acharya

NeurIPS 2021 Remember What You Want to Forget: Algorithms for Machine Unlearning Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh

ICML 2021 Robust Testing and Estimation Under Manipulation Attacks Jayadev Acharya, Ziteng Sun, Huanyu Zhang

ICML 2020 Context Aware Local Differential Privacy Jayadev Acharya, Kallista Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun

COLT 2020 Distributed Signal Detection Under Communication Constraints Jayadev Acharya, Clément L Canonne, Himanshu Tyagi

COLT 2020 Domain Compression and Its Application to Randomness-Optimal Distributed Goodness-of-Fit Jayadev Acharya, Clément L Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi

ALT 2020 Optimal Multiclass Overfitting by Sequence Reconstruction from Hamming Queries Jayadev Acharya, Ananda Theertha Suresh

ICML 2019 Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters Jayadev Acharya, Ziteng Sun

ICML 2019 Communication-Constrained Inference and the Role of Shared Randomness Jayadev Acharya, Clement Canonne, Himanshu Tyagi

ICML 2019 Distributed Learning with Sublinear Communication Jayadev Acharya, Chris De Sa, Dylan Foster, Karthik Sridharan

NeurIPS 2019 Estimating Entropy of Distributions in Constant Space Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun

AISTATS 2019 Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication Jayadev Acharya, Ziteng Sun, Huanyu Zhang

COLT 2019 Inference Under Information Constraints: Lower Bounds from Chi-Square Contraction Jayadev Acharya, Clément L Canonne, Himanshu Tyagi

AISTATS 2019 Test Without Trust: Optimal Locally Private Distribution Testing Jayadev Acharya, Clement Canonne, Cody Freitag, Himanshu Tyagi

NeurIPS 2018 Differentially Private Testing of Identity and Closeness of Discrete Distributions Jayadev Acharya, Ziteng Sun, Huanyu Zhang

ICML 2018 INSPECTRE: Privately Estimating the Unseen Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang

NeurIPS 2018 Learning and Testing Causal Models with Interventions Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy

JMLR 2018 Maximum Selection and Sorting with Adversarial Comparators Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

ICML 2017 A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh

ICML 2016 Fast Algorithms for Segmented Regression Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

NeurIPS 2015 Optimal Testing for Properties of Distributions Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath

NeurIPS 2014 Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour

AISTATS 2013 A Competitive Test for Uniformity of Monotone Distributions Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

COLT 2013 Optimal Probability Estimation with Applications to Prediction and Classification Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

COLT 2012 Competitive Classification and Closeness Testing Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Suresh

NeurIPS 2012 Tight Bounds on Profile Redundancy and Distinguishability Jayadev Acharya, Hirakendu Das, Alon Orlitsky

COLT 2011 Competitive Closeness Testing Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan