Odalric-Ambrym Maillard
Artificial Intelligence · 2009–2019
A researcher in the Science corpus: 8 papers; trusts 40 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it; #12,618 of 35,345 by trust here, #15,236 by citations
- Reinforcement Learning — 49 citations into it
- Statistics and Probability — 33 citations into it; #6,759 of 12,932 by trust here, #8,279 by citations
- Management Science and Operations Research — 30 citations into it; #5,885 of 11,946 by trust here, #4,921 by citations
- Statistical Learning Theory — 15 citations into it
- Control and Systems Engineering — 10 citations into it
- Optimization & Training — 10 citations into it
- Electrical and Electronic Engineering — 8 citations into it
Whom Odalric-Ambrym Maillard trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Vladimir Naumovich Vapni
- Martin L. Puterman
- Tong Zhang
- Richard S. Sutton
- Dimitri P. Bertsekas
- Nicolò Cesa-Bianchi
- Sham M. Kakade
- Andrew Barto
- Saharon Rosset
- R´emi Munos
Who trusts Odalric-Ambrym Maillard overall
- Jinglin Chen
- Hado van Hasselt
- Csaba Szepesvari
- Marc G. Bellemare
- Amir-massoud Farahmand
- Nan Jiang
- Alessandro Lazaric
- Hoang Minh Le
- Kaiqing Zhang
- Ian Waudby-Smith
Papers from Odalric-Ambrym Maillard's perspective
Ordered by how strongly the researchers Odalric-Ambrym Maillard 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)
- Gradient-based learning applied to document recognition
- Reinforcement Learning: An Introduction
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Regression Shrinkage and Selection via the Lasso
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Kullback–Leibler upper confidence bounds for optimal sequential allocation (2012) — 425 citations
- Concentration inequalities for sampling without replacement (2013) — 200 citations
- Scaling up budgeted reinforcement learning (2019) — 4 citations
- Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs (2018) — 79 citations
- Efficient tracking of a growing number of experts (2017) — 25 citations
- Finite-sample Analysis of Bellman Residual Minimization (2013)
- Finite-sample Analysis of Bellman Residual Minimization (2010) — 34 citations
- Compressed Least-Squares Regression (2009) — 117 citations