Jayadev Acharya

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 94

Top Venues

Publications

Yuhan Liu, Jayadev Acharya
The role of randomness in quantum state certification with unentangled measurements. COLT (2024)
Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh, Himanshu Tyagi
Optimal Rates for Nonparametric Density Estimation Under Communication Constraints. IEEE Trans. Inf. Theory 70 (3) (2024)
Yuhan Liu, Jayadev Acharya
The role of shared randomness in quantum state certification with unentangled measurements. CoRR (2024)
Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks. NeurIPS (2023)
Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun
Sample Complexity of Distinguishing Cause from Effect. AISTATS (2023)
Jayadev Acharya, Yuhan Liu, Ziteng Sun
Discrete Distribution Estimation under User-level Local Differential Privacy. AISTATS (2023)
Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi
Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints. NeurIPS (2023)
Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks. CoRR (2022)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi, Ziteng Sun
The Role of Interactivity in Structured Estimation. COLT (2022)
Jayadev Acharya, Yuhan Liu, Ziteng Sun
Discrete Distribution Estimation under User-level Local Differential Privacy. CoRR (2022)
Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi
The Role of Interactivity in Structured Estimation. CoRR (2022)
Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang
Robust Estimation for Random Graphs. COLT (2022)
Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi
Interactive Inference Under Information Constraints. IEEE Trans. Inf. Theory 68 (1) (2022)
Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi
Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition. NeurIPS (2021)
Sourbh Bhadane, Aaron B. Wagner, Jayadev Acharya
Principal Bit Analysis: Autoencoding with Schur-Concave Loss. CoRR (2021)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Robust Testing and Estimation under Manipulation Attacks. ICML (2021)
Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi
Interactive Inference under Information Constraints. ISIT (2021)
Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh, Himanshu Tyagi
Optimal Rates for Nonparametric Density Estimation under Communication Constraints. CoRR (2021)
Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi
Information-constrained optimization: can adaptive processing of gradients help? NeurIPS (2021)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Differentially Private Assouad, Fano, and Le Cam. ALT (2021)
Jayadev Acharya, Clément L. Canonne, Cody Freitag, Ziteng Sun, Himanshu Tyagi
Inference under Information Constraints III: Local Privacy Constraints. CoRR (2021)
Jayadev Acharya, Clément L. Canonne, Cody Freitag, Ziteng Sun, Himanshu Tyagi
Inference Under Information Constraints III: Local Privacy Constraints. IEEE J. Sel. Areas Inf. Theory 2 (1) (2021)
Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh, Himanshu Tyagi
Optimal Rates for Nonparametric Density Estimation under Communication Constraints. NeurIPS (2021)
Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh
Remember What You Want to Forget: Algorithms for Machine Unlearning. CoRR (2021)
Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh
Remember What You Want to Forget: Algorithms for Machine Unlearning. NeurIPS (2021)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Robust Testing and Estimation under Manipulation Attacks. CoRR (2021)
Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi
Information-constrained optimization: can adaptive processing of gradients help? CoRR (2021)
Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang
Robust Estimation for Random Graphs. CoRR (2021)
Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun
Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints. ALT (2021)
Sourbh Bhadane, Aaron B. Wagner, Jayadev Acharya
Principal Bit Analysis: Autoencoding with Schur-Concave Loss. ICML (2021)
Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun
Context Aware Local Differential Privacy. ICML (2020)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Inference Under Information Constraints I: Lower Bounds From Chi-Square Contraction. IEEE Trans. Inf. Theory 66 (12) (2020)
Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi
Unified lower bounds for interactive high-dimensional estimation under information constraints. CoRR (2020)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Differentially Private Assouad, Fano, and Le Cam. CoRR (2020)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Inference Under Information Constraints II: Communication Constraints and Shared Randomness. IEEE Trans. Inf. Theory 66 (12) (2020)
Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit. COLT (2020)
Jayadev Acharya, Ibrahim Issa, Nirmal V. Shende, Aaron B. Wagner
Estimating Quantum Entropy. IEEE J. Sel. Areas Inf. Theory 1 (2) (2020)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Distributed Signal Detection under Communication Constraints. COLT (2020)
Jayadev Acharya, Ananda Theertha Suresh
Optimal multiclass overfitting by sequence reconstruction from Hamming queries. ALT (2020)
Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang
INSPECTRE: Privately Estimating the Unseen. J. Priv. Confidentiality 10 (2) (2020)
Jayadev Acharya, Yuhan Liu, Ziteng Sun
Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints. CoRR (2020)
Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi
Interactive Inference under Information Constraints. CoRR (2020)
Jayadev Acharya, Ziteng Sun
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters. CoRR (2019)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Inference under Information Constraints: Lower Bounds from Chi-Square Contraction. COLT (2019)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Inference under Information Constraints II: Communication Constraints and Shared Randomness. CoRR (2019)
Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit. Electron. Colloquium Comput. Complex. 26 (2019)
Jayadev Acharya, Ziteng Sun
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters. ICML (2019)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Communication-Constrained Inference and the Role of Shared Randomness. ICML (2019)
Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit. CoRR (2019)
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun
Estimating Entropy of Distributions in Constant Space. CoRR (2019)
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun
Estimating Entropy of Distributions in Constant Space. NeurIPS (2019)
Jayadev Acharya, Ibrahim Issa, Nirmal V. Shende, Aaron B. Wagner
Measuring Quantum Entropy. ISIT (2019)
Jayadev Acharya, Christopher De Sa, Dylan J. Foster, Karthik Sridharan
Distributed Learning with Sublinear Communication. CoRR (2019)
Jayadev Acharya, Ananda Theertha Suresh
Optimal multiclass overfitting by sequence reconstruction from Hamming queries. CoRR (2019)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication. AISTATS (2019)
Jayadev Acharya, Chris De Sa, Dylan J. Foster, Karthik Sridharan
Distributed Learning with Sublinear Communication. ICML (2019)
Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun
Context-Aware Local Differential Privacy. CoRR (2019)
Jayadev Acharya, Clément L. Canonne, Cody Freitag, Himanshu Tyagi
Test without Trust: Optimal Locally Private Distribution Testing. AISTATS (2019)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation. CoRR (2018)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction. CoRR (2018)
Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Maximum Selection and Sorting with Adversarial Comparators. J. Mach. Learn. Res. 19 (2018)
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
Learning and Testing Causal Models with Interventions. CoRR (2018)
Jayadev Acharya
Profile Maximum Likelihood is Optimal for Estimating KL Divergence. ISIT (2018)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Differentially Private Testing of Identity and Closeness of Discrete Distributions. NeurIPS (2018)
Jayadev Acharya, Yelun Bao, Yuheng Kang, Ziteng Sun
Improved Bounds for Minimax Risk of Estimating Missing Mass. ISIT (2018)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Distributed Simulation and Distributed Inference. Electron. Colloquium Comput. Complex. 25 (2018)
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
Learning and Testing Causal Models with Interventions. NeurIPS (2018)
Jayadev Acharya, Clément L. Canonne, Gautam Kamath
A Chasm Between Identity and Equivalence Testing with Conditional Queries. Theory Comput. 14 (1) (2018)
Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang
INSPECTRE: Privately Estimating the Unseen. ICML (2018)
Jayadev Acharya, Clément L. Canonne, Cody Freitag, Himanshu Tyagi
Test without Trust: Optimal Locally Private Distribution Testing. CoRR (2018)
Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang
INSPECTRE: Privately Estimating the Unseen. CoRR (2018)
Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi
Distributed Simulation and Distributed Inference. CoRR (2018)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions. ICML (2017)
Jayadev Acharya, Ibrahim Issa, Nirmal V. Shende, Aaron B. Wagner
Measuring Quantum Entropy. CoRR (2017)
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Differentially Private Testing of Identity and Closeness of Discrete Distributions. CoRR (2017)
Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
Sample-Optimal Density Estimation in Nearly-Linear Time. SODA (2017)
Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath
Improved bounds for universal one-bit compressive sensing. ISIT (2017)
Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
Estimating Renyi Entropy of Discrete Distributions. IEEE Trans. Inf. Theory 63 (1) (2017)
Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath
Improved Bounds for Universal One-Bit Compressive Sensing. CoRR (2017)
Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
Fast Algorithms for Segmented Regression. ICML (2016)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. CoRR (2016)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. Electron. Colloquium Comput. Complex. 23 (2016)
Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath
A Framework for Testing Properties of Discrete Distributions: Monotonicity, Independence, and More. Tiny Trans. Comput. Sci. 4 (2016)
Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
Fast Algorithms for Segmented Regression. CoRR (2016)
Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Maximum Selection and Sorting with Adversarial Comparators and an Application to Density Estimation. CoRR (2016)
Jayadev Acharya, Clément L. Canonne, Gautam Kamath
Adaptive estimation in weighted group testing. ISIT (2015)
Jayadev Acharya, Ilias Diakonikolas, Chinmay Hegde, Jerry Zheng Li, Ludwig Schmidt
Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms. PODS (2015)
Jayadev Acharya, Constantinos Daskalakis
Testing Poisson Binomial Distributions. SODA (2015)
Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
The Complexity of Estimating Rényi Entropy. SODA (2015)
Jayadev Acharya, Clément L. Canonne, Gautam Kamath
A Chasm Between Identity and Equivalence Testing with Conditional Queries. APPROX-RANDOM (2015)
Jayadev Acharya, Ilias Diakonikolas, Jerry Zheng Li, Ludwig Schmidt
Sample-Optimal Density Estimation in Nearly-Linear Time. CoRR (2015)
Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan
String Reconstruction from Substring Compositions. SIAM J. Discret. Math. 29 (3) (2015)
Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath
Optimal Testing for Properties of Distributions. CoRR (2015)
Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath
Optimal Testing for Properties of Distributions. NIPS (2015)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Near-optimal-sample estimators for spherical Gaussian mixtures. CoRR (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Efficient compression of monotone and m-modal distributions. ISIT (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Sublinear algorithms for outlier detection and generalized closeness testing. ISIT (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Universal Compression of Envelope Classes: Tight Characterization via Poisson Sampling. CoRR (2014)
Jayadev Acharya, Clément L. Canonne, Gautam Kamath
A Chasm Between Identity and Equivalence Testing with Conditional Queries. Electron. Colloquium Comput. Complex. 21 (2014)
Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour
Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures. NIPS (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jayadev Acharya