Jayadev Acharya

According to our database, Jayadev Acharya authored at least 81 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Optimal Rates for Nonparametric Density Estimation Under Communication Constraints.

Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2024

Quantum state testing with restricted measurements.

Yuhan Liu, Jayadev Acharya

CoRR, 2024

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

Yuhan Liu, Jayadev Acharya

CoRR, 2024

The role of randomness in quantum state certification with unentangled measurements.

Yuhan Liu, Jayadev Acharya

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks.

Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari

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.

Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi

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.

Jayadev Acharya, Yuhan Liu, Ziteng Sun

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Sample Complexity of Distinguishing Cause from Effect.

Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Interactive Inference Under Information Constraints.

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

IEEE Trans. Inf. Theory, 2022

Robust Estimation for Random Graphs.

Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

The Role of Interactivity in Structured Estimation.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi, Ziteng Sun

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Inference Under Information Constraints III: Local Privacy Constraints.

Jayadev Acharya, Clément L. Canonne, Cody Freitag, Ziteng Sun, Himanshu Tyagi

IEEE J. Sel. Areas Inf. Theory, 2021

Remember What You Want to Forget: Algorithms for Machine Unlearning.

Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh

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?

Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi

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.

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

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.

Sourbh Bhadane, Aaron B. Wagner, Jayadev Acharya

Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Testing and Estimation under Manipulation Attacks.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

Differentially Private Assouad, Fano, and Le Cam.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the Algorithmic Learning Theory, 2021

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints.

Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun

Proceedings of the Algorithmic Learning Theory, 2021

2020

Inference Under Information Constraints II: Communication Constraints and Shared Randomness.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2020

Inference Under Information Constraints I: Lower Bounds From Chi-Square Contraction.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2020

Estimating Quantum Entropy.

Jayadev Acharya, Ibrahim Issa, Nirmal V. Shende, Aaron B. Wagner

IEEE J. Sel. Areas Inf. Theory, 2020

INSPECTRE: Privately Estimating the Unseen.

Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang

J. Priv. Confidentiality, 2020

Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints.

Jayadev Acharya, Yuhan Liu, Ziteng Sun

CoRR, 2020

Context Aware Local Differential Privacy.

Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun

Proceedings of the 37th International Conference on Machine Learning, 2020

Distributed Signal Detection under Communication Constraints.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Proceedings of the Conference on Learning Theory, 2020

Optimal multiclass overfitting by sequence reconstruction from Hamming queries.

Jayadev Acharya, Ananda Theertha Suresh

Proceedings of the Algorithmic Learning Theory, 2020

2019

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

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

Electron. Colloquium Comput. Complex., 2019

Estimating Entropy of Distributions in Constant Space.

Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Measuring Quantum Entropy.

Jayadev Acharya, Ibrahim Issa, Nirmal V. Shende, Aaron B. Wagner

Proceedings of the IEEE International Symposium on Information Theory, 2019

Distributed Learning with Sublinear Communication.

Jayadev Acharya, Chris De Sa, Dylan J. Foster, Karthik Sridharan

Proceedings of the 36th International Conference on Machine Learning, 2019

Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters.

Jayadev Acharya, Ziteng Sun

Proceedings of the 36th International Conference on Machine Learning, 2019

Communication-Constrained Inference and the Role of Shared Randomness.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Proceedings of the 36th International Conference on Machine Learning, 2019

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

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Proceedings of the Conference on Learning Theory, 2019

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

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Test without Trust: Optimal Locally Private Distribution Testing.

Jayadev Acharya, Clément L. Canonne, Cody Freitag, Himanshu Tyagi

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Maximum Selection and Sorting with Adversarial Comparators.

Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

J. Mach. Learn. Res., 2018

Distributed Simulation and Distributed Inference.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Electron. Colloquium Comput. Complex., 2018

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

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

CoRR, 2018

Differentially Private Testing of Identity and Closeness of Discrete Distributions.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

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.

Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy

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.

Jayadev Acharya, Yelun Bao, Yuheng Kang, Ziteng Sun

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Profile Maximum Likelihood is Optimal for Estimating KL Divergence.

Jayadev Acharya

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

Estimating Renyi Entropy of Discrete Distributions.

Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2017

Sample-Optimal Density Estimation in Nearly-Linear Time.

Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 2017

Improved bounds for universal one-bit compressive sensing.

Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

A Framework for Testing Properties of Discrete Distributions: Monotonicity, Independence, and More.

Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath

Tiny Trans. Comput. Sci., 2016

A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh

Electron. Colloquium Comput. Complex., 2016

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

Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

CoRR, 2016

Fast Algorithms for Segmented Regression.

Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

String Reconstruction from Substring Compositions.

Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan

SIAM J. Discret. Math., 2015

The Complexity of Estimating Rényi Entropy.

Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Testing Poisson Binomial Distributions.

Jayadev Acharya, Constantinos Daskalakis

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms.

Jayadev Acharya, Ilias Diakonikolas, Chinmay Hegde, Jerry Zheng Li, Ludwig Schmidt

Proceedings of the 34th ACM Symposium on Principles of Database Systems, 2015

Optimal Testing for Properties of Distributions.

Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath

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.

Jayadev Acharya, Clément L. Canonne, Gautam Kamath

Proceedings of the IEEE International Symposium on Information Theory, 2015

2014

A Chasm Between Identity and Equivalence Testing with Conditional Queries.

Jayadev Acharya, Clément L. Canonne, Gautam Kamath

Electron. Colloquium Comput. Complex., 2014

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

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

CoRR, 2014

Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures.

Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour

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.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Poissonization and universal compression of envelope classes.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Efficient compression of monotone and m-modal distributions.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

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.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

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.

Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan

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.

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Optimal Probability Estimation with Applications to Prediction and Classification.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the COLT 2013, 2013

A Competitive Test for Uniformity of Monotone Distributions.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Competitive Classification and Closeness Testing.

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh

Proceedings of the COLT 2012, 2012

Tight Bounds on Profile Redundancy and Distinguishability.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky

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.

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011

Competitive Closeness Testing.

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan

Proceedings of the COLT 2011, 2011

Algebraic computation of pattern maximum likelihood.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Shengjun Pan

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Expected query complexity of symmetric boolean functions.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky

Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010

Classification using pattern probability estimators.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Shengjun Pan, Narayana P. Santhanam

Proceedings of the IEEE International Symposium on Information Theory, 2010

Exact calculation of pattern probabilities.

Jayadev Acharya, Hirakendu Das, Hosein Mohimani, Alon Orlitsky, Shengjun Pan

Proceedings of the IEEE International Symposium on Information Theory, 2010

On reconstructing a string from its substring compositions.

Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan

Proceedings of the IEEE International Symposium on Information Theory, 2010

2009

Recent results on pattern maximum likelihood.

Jayadev Acharya, Alon Orlitsky, Shengjun Pan

Proceedings of the 2009 IEEE Information Theory Workshop, 2009

The maximum likelihood probability of unique-singleton, ternary, and length-7 patterns.

Shengjun Pan, Jayadev Acharya, Alon Orlitsky

Proceedings of the IEEE International Symposium on Information Theory, 2009

2008

Multilevel thresholding for image segmentation through a fast statistical recursive algorithm.

Siddharth Arora, Jayadev Acharya, Amit Verma, Prasanta K. Panigrahi

Pattern Recognit. Lett., 2008

2007

A Fast Hierarchical Multilevel Image Segmentation Method using Unbiased Estimators

Sreechakra Goparaju, Jayadev Acharya, Ajoy K. Ray, Jaideva C. Goswami

CoRR, 2007