Levente Kocsis

Artificial Intelligence · 2006–2018

A researcher in the Science corpus: 4 papers; trusts 88 researchers and is trusted by 386 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 81 citations into it; #844 of 35,345 by trust here, #3,273 by citations
• Information Systems — 39 citations into it
• Computer Networks and Communications — 23 citations into it; #3,792 of 9,886 by trust here, #7,492 by citations
• Signal Processing — 23 citations into it
• Management Science and Operations Research — 20 citations into it; #57 of 11,946 by trust here, #257 by citations
• Reinforcement Learning — 17 citations into it; #102 of 2,242 by trust here, #349 by citations
• Computer Vision and Pattern Recognition — 15 citations into it
• ML Systems & Hardware — 11 citations into it

Whom Levente Kocsis trusts overall

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

1. Albert Bifet
2. Richard S. Sutton
3. Alex Smola
4. Peter Auer
5. Ronald J. Williams
6. Geoffrey E. Hinton
7. Yoav Freund
8. Nicolò Cesa-Bianchi
9. Stephen J. J. Smith
10. Steffen Rendle

Who trusts Levente Kocsis overall

1. David Silver
2. Peter Stone
3. Todd Hester
4. R´emi Munos
5. Nan Jiang
6. Erik Talvitie
7. Michael L. Littman
8. Johannes Heinrich
9. Yuxi Li
10. Martin Wistuba

Papers from Levente Kocsis's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Bandit Based Monte-Carlo Planning (2006) — 3,947 citations
• The grand challenge of computer Go (2012) — 240 citations
• Efficient Multi-Start Strategies for Local Search Algorithms (2009) — 95 citations
• Online Machine Learning in Big Data Streams (2018) — 47 citations