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Robust Testing and Estimation under Manipulation Attacks


Apr 21, 2021
Jayadev Acharya, Ziteng Sun, Huanyu Zhang


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Remember What You Want to Forget: Algorithms for Machine Unlearning


Mar 04, 2021
Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh


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General lower bounds for interactive high-dimensional estimation under information constraints


Nov 11, 2020
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

* Fixing an issue the proof of Lemma 8, where arguments were incorrectly swapped. Introducing Assumption 2 

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Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints


Oct 30, 2020
Jayadev Acharya, Yuhan Liu, Ziteng Sun


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Interactive Inference under Information Constraints


Aug 18, 2020
Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi

* Fixed a typo in the table of results ("k" in the denominator of one expression should have been "sqrt(k)") 

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Differentially Private Assouad, Fano, and Le Cam


Apr 17, 2020
Jayadev Acharya, Ziteng Sun, Huanyu Zhang


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Estimating Entropy of Distributions in Constant Space


Nov 18, 2019
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun

* NeurIPS 2019 

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Context-Aware Local Differential Privacy


Oct 31, 2019
Jayadev Acharya, Keith Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun


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Optimal multiclass overfitting by sequence reconstruction from Hamming queries


Aug 08, 2019
Jayadev Acharya, Ananda Theertha Suresh


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Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit


Jul 20, 2019
Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi


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Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters


May 28, 2019
Jayadev Acharya, Ziteng Sun

* ICML 2019 

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Inference under Information Constraints II: Communication Constraints and Shared Randomness


May 20, 2019
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

* An abridged version of this work will appear in the 2019 International Conference on Machine Learning (ICML) 

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Distributed Learning with Sublinear Communication


Mar 18, 2019
Jayadev Acharya, Christopher De Sa, Dylan J. Foster, Karthik Sridharan


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Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction


Dec 30, 2018
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi


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Distributed Simulation and Distributed Inference


Aug 10, 2018
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

* Improved presentation, and added a "smooth" protocol for uniformity testing 

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Test without Trust: Optimal Locally Private Distribution Testing


Aug 07, 2018
Jayadev Acharya, Clément L. Canonne, Cody Freitag, Himanshu Tyagi


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Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication


Jun 27, 2018
Jayadev Acharya, Ziteng Sun, Huanyu Zhang


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Learning and Testing Causal Models with Interventions


May 24, 2018
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy


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INSPECTRE: Privately Estimating the Unseen


Feb 28, 2018
Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang


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Differentially Private Testing of Identity and Closeness of Discrete Distributions


Oct 31, 2017
Jayadev Acharya, Ziteng Sun, Huanyu Zhang


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A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation


Nov 28, 2016
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh


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Fast Algorithms for Segmented Regression


Jul 14, 2016
Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

* 27 pages, appeared in ICML 2016 

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Estimating Renyi Entropy of Discrete Distributions


Mar 10, 2016
Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi


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Optimal Testing for Properties of Distributions


Dec 08, 2015
Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath

* 31 pages, extended abstract appeared as a spotlight in NIPS 2015 

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Sample-Optimal Density Estimation in Nearly-Linear Time


Jun 01, 2015
Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt


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