Alibek Sailanbayev

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #13,811 of 35,345 by trust here, #15,542 by citations
• Optimization & Training — 29 citations into it; #1,323 of 2,601 by trust here, #1,419 by citations
• Computational Mechanics — 21 citations into it
• Statistics and Probability — 9 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Alibek Sailanbayev trusts overall

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

1. Peter Richtárik
2. Zheng Qu
3. Deanna Needell
4. Yurii E. Nesterov
5. Dimitri P. Bertsekas
6. Chih-Jen Lin
7. Martin Takác
8. Shai Shalev-Shwartz

Who trusts Alibek Sailanbayev overall

1. Nicolas Loizou
2. Peter Richtárik
3. Ahmed Khaled
4. Filip Hanzely

Papers from Alibek Sailanbayev's perspective

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

1. A Stochastic Approximation Method
2. Stochastic Approximation approach to Stochastic Programming
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Pegasos: primal estimated sub-gradient solver for SVM
8. LIBSVM: A library for support vector machines
9. ImageNet classification with deep convolutional neural networks
10. Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning

Their papers

• SGD: General Analysis and Improved Rates (2019) — 484 citations