Ilias Diakonikolas
Artificial Intelligence · 2010–2019
A researcher in the Science corpus: 23 papers; trusts 125 researchers and is trusted by 60 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 196 citations into it; #2,798 of 35,345 by trust here, #2,908 by citations
- Statistics and Probability — 146 citations into it; #1,767 of 12,932 by trust here, #776 by citations
- Computational Theory and Mathematics — 62 citations into it; #2,212 of 12,182 by trust here, #2,201 by citations
- Statistical Learning Theory — 44 citations into it; #486 of 1,038 by trust here, #243 by citations
- Computational Mechanics — 32 citations into it
- Safety, Robustness & Interpretability — 24 citations into it; #1,877 of 2,251 by trust here, #1,349 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Applied Mathematics — 17 citations into it
Whom Ilias Diakonikolas trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Leslie G. Valiant
- Michael Kearns
- Gregory Valiant
- Daniel M. Kane
- Oded Goldreich
- Gautam Kamath
- Jacob Steinhardt
- Ankur Moitra
- Kevin A. Lai
- Vitaly Feldman
Who trusts Ilias Diakonikolas overall
- Jayadev Acharya
- Gautam Kamath
- Daniel M. Kane
- Clément Louis Canonne
- Jerry Zheng Li
- Alistair Stewart
- Sivaraman Balakrishnan
- Yu Cheng
- Saeed Mahloujifar
- Jacob Steinhardt
Papers from Ilias Diakonikolas's perspective
Ordered by how strongly the researchers Ilias Diakonikolas 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
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Et al
Their papers
- Robust Estimators in High Dimensions without the Computational Intractability (2016) — 568 citations
- Sever: A Robust Meta-Algorithm for Stochastic Optimization (2018) — 319 citations
- Being Robust (in High Dimensions) Can Be Practical (2017) — 267 citations
- High-Dimensional Robust Mean Estimation in Nearly-Linear Time (2018) — 132 citations
- Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures (2016) — 254 citations
- Optimal Algorithms for Testing Closeness of Discrete Distributions (2013) — 245 citations
- List-decodable robust mean estimation and learning mixtures of spherical gaussians (2017) — 160 citations
- Robustly Learning a Gaussian: Getting Optimal Error, Efficiently (2017) — 142 citations
- Testing Shape Restrictions of Discrete Distributions (2015) — 90 citations
- Communication and Memory Efficient Testing of Discrete Distributions (2019) — 31 citations
- Differentially Private Identity and Equivalence Testing of Discrete Distributions (2018) — 32 citations
- Efficient Algorithms and Lower Bounds for Robust Linear Regression (2018) — 174 citations
- Differentially Private Identity and Closeness Testing of Discrete Distributions (2017) — 15 citations
- Learning geometric concepts with nasty noise (2017) — 108 citations
- Communication-Efficient Distributed Learning of Discrete Distributions (2017) — 34 citations
- Communication-Efficient Distributed Learning of Discrete Probability Distributions (2017)
- Sample-Optimal Identity Testing with High Probability (2017) — 70 citations
- Robust Learning of Fixed-Structure Bayesian Networks (2016) — 47 citations
- Efficient Robust Proper Learning of Log-concave Distributions (2016) — 30 citations
- Learning Structured Distributions (2016) — 69 citations