Ilja Kuzborskij

Artificial Intelligence · 2013–2017

A researcher in the Science corpus: 3 papers; trusts 99 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #10,070 of 35,345 by trust here, #12,974 by citations
• Computer Vision and Pattern Recognition — 16 citations into it
• Optimization & Training — 16 citations into it
• Computational Mechanics — 13 citations into it; #3,674 of 10,001 by trust here, #6,582 by citations
• Representation & Self-Supervised Learning — 11 citations into it; #1,733 of 3,145 by trust here, #1,913 by citations
• Statistical Learning Theory — 9 citations into it
• Management Science and Operations Research — 7 citations into it
• Statistics and Probability — 6 citations into it; #5,251 of 12,932 by trust here, #7,508 by citations

Whom Ilja Kuzborskij trusts overall

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

1. Olivier Bousquet
2. Radford M. Neal
3. Francesco Orabona
4. Barak A. Pearlmutter
5. Shai Shalev-Shwartz
6. Jun Yang
7. Ben London
8. Tatiana Tommasi
9. Hal Daumé Iii
10. Geoffrey E. Hinton

Who trusts Ilja Kuzborskij overall

1. Yu Zhang
2. Han-Jia Ye
3. Yu-Xiong Wang
4. Steve Hanneke
5. Michaël Perrot
6. Francesco Orabona
7. Kenji Kawaguchi
8. Huaxiu Yao
9. Da-Wei Zhou
10. Vitaly Feldman

Papers from Ilja Kuzborskij's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Data-Dependent Stability of Stochastic Gradient Descent (2017) — 192 citations
• From N to N+1: Multiclass Transfer Incremental Learning (2013) — 151 citations
• Stability and Hypothesis Transfer Learning (2013) — 195 citations