Alistair Stewart
Artificial Intelligence · 2016–2018
A researcher in the Science corpus: 10 papers; trusts 50 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 99 citations into it; #4,348 of 35,345 by trust here, #3,797 by citations
- Statistics and Probability — 71 citations into it; #1,748 of 12,932 by trust here, #776 by citations
- Statistical Learning Theory — 30 citations into it; #467 of 1,038 by trust here, #243 by citations
- Computational Mechanics — 24 citations into it
- Safety, Robustness & Interpretability — 22 citations into it; #1,779 of 2,251 by trust here, #1,349 by citations
- Computational Theory and Mathematics — 21 citations into it
- Signal Processing — 14 citations into it
- Computer Vision and Pattern Recognition — 13 citations into it
Whom Alistair Stewart trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilias Diakonikolas
- Leslie G. Valiant
- Michael Kearns
- Daniel M. Kane
- Vitaly Feldman
- Gautam Kamath
- Ankur Moitra
- Adam R. Klivans
- Jacob Steinhardt
- Roman Vershynin
Who trusts Alistair Stewart overall
- Ilias Diakonikolas
- Daniel M. Kane
- Jerry Zheng Li
- Gautam Kamath
- Yu Cheng
- Saeed Mahloujifar
- Jacob Steinhardt
- Sivaraman Balakrishnan
- Gábor Lugosi
- Dong Yin
Papers from Alistair Stewart's perspective
Ordered by how strongly the researchers Alistair Stewart 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
- Et al
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning in the presence of malicious errors
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
- Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures (2016) — 254 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
- Efficient Algorithms and Lower Bounds for Robust Linear Regression (2018) — 174 citations
- Learning geometric concepts with nasty noise (2017) — 108 citations
- Robust Learning of Fixed-Structure Bayesian Networks (2016) — 47 citations
- Efficient Robust Proper Learning of Log-concave Distributions (2016) — 30 citations