Jayadev Acharya

Artificial Intelligence · 2006–2021

A researcher in the Science corpus: 19 papers; trusts 156 researchers and is trusted by 45 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 382 citations into it; #3,347 of 35,345 by trust here, #4,526 by citations
Statistics and Probability — 185 citations into it; #2,206 of 12,932 by trust here, #2,069 by citations
Privacy & Security — 154 citations into it; #173 of 709 by trust here, #323 by citations
Computational Theory and Mathematics — 106 citations into it; #6,232 of 12,182 by trust here, #6,165 by citations
Statistical Learning Theory — 58 citations into it
Electrical and Electronic Engineering — 51 citations into it; #724 of 16,539 by trust here, #4,925 by citations
Computer Networks and Communications — 49 citations into it; #1,706 of 9,886 by trust here, #1,912 by citations
Safety, Robustness & Interpretability — 38 citations into it

Whom Jayadev Acharya trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Jayadev Acharya overall

Papers from Jayadev Acharya's perspective

Ordered by how strongly the researchers Jayadev Acharya trusts endorse each paper. Same corpus, a different order for every researcher.

Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
ImageNet classification with deep convolutional neural networks
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Gradient-based learning applied to document recognition
Learning Multiple Layers of Features from Tiny Images
ImageNet: A large-scale hierarchical image database
Long Short-Term Memory
Attention is All you Need (Neural Information Processing Systems)
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Calibrating Noise to Sensitivity in Private Data Analysis

Their papers

Remember What You Want to Forget: Algorithms for Machine Unlearning (2021) — 475 citations
Inference Under Information Constraints I: Lower Bounds From Chi-Square Contraction (2018) — 126 citations
Differentially Private Testing of Identity and Closeness of Discrete Distributions (2017) — 83 citations
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters (2019) — 62 citations
Distributed Simulation and Distributed Inference (2018) — 26 citations
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit (2019) — 28 citations
Inference Under Information Constraints II: Communication Constraints and Shared Randomness (2019) — 66 citations
Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation (2018) — 26 citations
INSPECTRE: Privately Estimating the Unseen (2018) — 23 citations
Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints (2020) — 5 citations
Differentially Private Assouad, Fano, and Le Cam (2020) — 76 citations
Inference Under Information Constraints III: Local Privacy Constraints (2021) — 40 citations
Unified lower bounds for interactive high-dimensional estimation under information constraints (2020) — 41 citations
Distributed Signal Detection under Communication Constraints (2020) — 26 citations
Test without Trust: Optimal Locally Private Distribution Testing (2018) — 64 citations
Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication (2018) — 173 citations
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions (2017) — 64 citations
Estimating Renyi Entropy of Discrete Distributions (2014) — 84 citations
Multilevel thresholding for image segmentation through a fast statistical recursive algorithm (2006) — 318 citations