Jayadev Acharya

Orcid: 0000-0003-2170-3015

According to our database1, Jayadev Acharya authored at least 79 papers between 2007 and 2024.

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Bibliography

2024
Optimal Rates for Nonparametric Density Estimation Under Communication Constraints.
IEEE Trans. Inf. Theory, 2024

The role of shared randomness in quantum state certification with unentangled measurements.
CoRR, 2024

2023
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discrete Distribution Estimation under User-level Local Differential Privacy.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Sample Complexity of Distinguishing Cause from Effect.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Interactive Inference Under Information Constraints.
IEEE Trans. Inf. Theory, 2022

Robust Estimation for Random Graphs.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

The Role of Interactivity in Structured Estimation.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Inference Under Information Constraints III: Local Privacy Constraints.
IEEE J. Sel. Areas Inf. Theory, 2021

Remember What You Want to Forget: Algorithms for Machine Unlearning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Information-constrained optimization: can adaptive processing of gradients help?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Principal Bit Analysis: Autoencoding with Schur-Concave Loss.
Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Testing and Estimation under Manipulation Attacks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Differentially Private Assouad, Fano, and Le Cam.
Proceedings of the Algorithmic Learning Theory, 2021

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints.
Proceedings of the Algorithmic Learning Theory, 2021

2020
Inference Under Information Constraints II: Communication Constraints and Shared Randomness.
IEEE Trans. Inf. Theory, 2020

Inference Under Information Constraints I: Lower Bounds From Chi-Square Contraction.
IEEE Trans. Inf. Theory, 2020

Estimating Quantum Entropy.
IEEE J. Sel. Areas Inf. Theory, 2020

INSPECTRE: Privately Estimating the Unseen.
J. Priv. Confidentiality, 2020

Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints.
CoRR, 2020

Context Aware Local Differential Privacy.
Proceedings of the 37th International Conference on Machine Learning, 2020

Distributed Signal Detection under Communication Constraints.
Proceedings of the Conference on Learning Theory, 2020

Optimal multiclass overfitting by sequence reconstruction from Hamming queries.
Proceedings of the Algorithmic Learning Theory, 2020

2019
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit.
Electron. Colloquium Comput. Complex., 2019

Estimating Entropy of Distributions in Constant Space.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Measuring Quantum Entropy.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Distributed Learning with Sublinear Communication.
Proceedings of the 36th International Conference on Machine Learning, 2019

Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters.
Proceedings of the 36th International Conference on Machine Learning, 2019

Communication-Constrained Inference and the Role of Shared Randomness.
Proceedings of the 36th International Conference on Machine Learning, 2019

Inference under Information Constraints: Lower Bounds from Chi-Square Contraction.
Proceedings of the Conference on Learning Theory, 2019

Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Test without Trust: Optimal Locally Private Distribution Testing.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Chasm Between Identity and Equivalence Testing with Conditional Queries.
Theory Comput., 2018

Maximum Selection and Sorting with Adversarial Comparators.
J. Mach. Learn. Res., 2018

Distributed Simulation and Distributed Inference.
Electron. Colloquium Comput. Complex., 2018

Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation.
CoRR, 2018

Differentially Private Testing of Identity and Closeness of Discrete Distributions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning and Testing Causal Models with Interventions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Improved Bounds for Minimax Risk of Estimating Missing Mass.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Profile Maximum Likelihood is Optimal for Estimating KL Divergence.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017
Estimating Renyi Entropy of Discrete Distributions.
IEEE Trans. Inf. Theory, 2017

Sample-Optimal Density Estimation in Nearly-Linear Time.
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 2017

Improved bounds for universal one-bit compressive sensing.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
A Framework for Testing Properties of Discrete Distributions: Monotonicity, Independence, and More.
Tiny Trans. Comput. Sci., 2016

A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation.
Electron. Colloquium Comput. Complex., 2016

Maximum Selection and Sorting with Adversarial Comparators and an Application to Density Estimation.
CoRR, 2016

Fast Algorithms for Segmented Regression.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
String Reconstruction from Substring Compositions.
SIAM J. Discret. Math., 2015

The Complexity of Estimating Rényi Entropy.
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Testing Poisson Binomial Distributions.
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms.
Proceedings of the 34th ACM Symposium on Principles of Database Systems, 2015

Optimal Testing for Properties of Distributions.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Adaptive estimation in weighted group testing.
Proceedings of the IEEE International Symposium on Information Theory, 2015

2014
Universal Compression of Envelope Classes: Tight Characterization via Poisson Sampling.
CoRR, 2014

Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Sublinear algorithms for outlier detection and generalized closeness testing.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Poissonization and universal compression of envelope classes.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Efficient compression of monotone and m-modal distributions.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Sorting with adversarial comparators and application to density estimation.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Quadratic-backtracking algorithm for string reconstruction from substring compositions.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013
Tight bounds for universal compression of large alphabets.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Optimal Probability Estimation with Applications to Prediction and Classification.
Proceedings of the COLT 2013, 2013

A Competitive Test for Uniformity of Monotone Distributions.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Competitive Classification and Closeness Testing.
Proceedings of the COLT 2012, 2012

Tight Bounds on Profile Redundancy and Distinguishability.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Estimating multiple concurrent processes.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011
Competitive Closeness Testing.
Proceedings of the COLT 2011, 2011

Algebraic computation of pattern maximum likelihood.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Expected query complexity of symmetric boolean functions.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010
Classification using pattern probability estimators.
Proceedings of the IEEE International Symposium on Information Theory, 2010

Exact calculation of pattern probabilities.
Proceedings of the IEEE International Symposium on Information Theory, 2010

On reconstructing a string from its substring compositions.
Proceedings of the IEEE International Symposium on Information Theory, 2010

2009
Recent results on pattern maximum likelihood.
Proceedings of the 2009 IEEE Information Theory Workshop, 2009

The maximum likelihood probability of unique-singleton, ternary, and length-7 patterns.
Proceedings of the IEEE International Symposium on Information Theory, 2009

2008
Multilevel thresholding for image segmentation through a fast statistical recursive algorithm.
Pattern Recognit. Lett., 2008

2007
A Fast Hierarchical Multilevel Image Segmentation Method using Unbiased Estimators
CoRR, 2007


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