Dominik Csiba
Artificial Intelligence · 2015–2016
A researcher in the Science corpus: 4 papers; trusts 58 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 98 citations into it; #4,711 of 35,345 by trust here, #11,750 by citations
- Optimization & Training — 80 citations into it; #1,191 of 2,601 by trust here, #1,942 by citations
- Computational Mechanics — 76 citations into it; #1,849 of 10,001 by trust here, #3,763 by citations
- Statistics and Probability — 32 citations into it; #1,496 of 12,932 by trust here, #2,407 by citations
- Mathematical Optimization — 21 citations into it
- Computational Theory and Mathematics — 14 citations into it
- Management Science and Operations Research — 11 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
Whom Dominik Csiba trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Peter Richtárik
- Shai Shalev-Shwartz
- Tong Zhang
- Martin Takác
- Yurii E. Nesterov
- Zheng Qu
- Jakub Konecný
- Rie Johnson
- Julien Mairal
- Mark W. Schmidt
Who trusts Dominik Csiba overall
- Jakub Konecný
- Peter Richtárik
- Samuel Horváth
- Konstantin Mishchenko
- Dmitry Kovalev
- Filip Hanzely
- Julie Nutini
- Martin Jaggi
- Sebastian U. Stich
- Hyun-woo Koh
Papers from Dominik Csiba's perspective
Ordered by how strongly the researchers Dominik Csiba trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Importance Sampling for Minibatches (2016) — 134 citations
- Stochastic Dual Coordinate Ascent with Adaptive Probabilities (2015) — 98 citations
- Coordinate Descent Face-Off: Primal or Dual? (2016) — 12 citations
- Primal Method for ERM with Flexible Mini-batching Schemes and Non-convex Losses (2015) — 23 citations