Marc Schoenauer
Artificial Intelligence · with Sebag · 2000–2019
A researcher in the Science corpus: 10 papers; trusts 145 researchers and is trusted by 37 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 107 citations into it; #7,121 of 35,345 by trust here, #6,157 by citations
- Computer Vision and Pattern Recognition — 48 citations into it
- Optimization & Training — 39 citations into it
- Reinforcement Learning — 37 citations into it; #649 of 2,242 by trust here, #769 by citations
- Representation & Self-Supervised Learning — 32 citations into it
- Management Science and Operations Research — 12 citations into it
- Control and Systems Engineering — 10 citations into it
- Statistical Learning Theory — 9 citations into it
Whom Marc Schoenauer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- Richard S. Sutton
- Nikolaus Hansen
- Diederik P. Kingma
- Andrew Y. Ng
- Yann LeCun
- Ilya Sutskever
- R´emi Munos
Who trusts Marc Schoenauer overall
- Christian Wirth
- Agoston E. Eiben
- Jan Leike
- Riad Akrour
- Ellen R. Novoseller
- Paul Christiano
- Róbert Istvan Busa-Fekete
- Ruohan Zhang
- Johannes Fürnkranz
- Christian Daniel
Papers from Marc Schoenauer's perspective
Ordered by how strongly the researchers Marc Schoenauer 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
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- The grand challenge of computer Go (2012) — 240 citations
- The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities (2018) — 317 citations
- APRIL: Active Preference-learning based Reinforcement Learning (2012) — 126 citations
- Parameter Control in Evolutionary Algorithms (2007) — 2,017 citations
- Multi-Domain Adversarial Learning (2019) — 65 citations
- Stochastic Gradient Descent: Going As Fast As Possible But Not Faster (2017) — 14 citations
- Evolutionary Computation (2017) — 425 citations
- Programming by Feedback (2014) — 72 citations
- Preference-Based Policy Learning (2011)
- Parallel Problem Solving from Nature PPSN VI (2000) — 650 citations