Nicholas Jacek

Artificial Intelligence · 2013–2014

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it
• Reinforcement Learning — 33 citations into it
• Optimization & Training — 30 citations into it
• Computational Mechanics — 17 citations into it
• Computational Theory and Mathematics — 17 citations into it
• Mathematical Optimization — 13 citations into it
• Management Science and Operations Research — 11 citations into it
• Numerical Analysis — 8 citations into it

Whom Nicholas Jacek trusts overall

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

1. Richard S. Sutton
2. Dimitri P. Bertsekas
3. Stephen W. Carden
4. Sridhar Mahadevan
5. Michail G. Lagoudakis
6. Amir Beck
7. J. Kolter
8. Andrew Barto
9. Yurii E. Nesterov
10. George Dimitri Konidaris

Papers from Nicholas Jacek's perspective

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

1. Reinforcement Learning: An Introduction
2. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
3. ImageNet classification with deep convolutional neural networks
4. Linear Least-Squares algorithms for temporal difference learning
5. Policy Gradient Methods for Reinforcement Learning with Function Approximation
6. Gradient-based learning applied to document recognition
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Residual Algorithms: Reinforcement Learning with Function Approximation
9. Parallel and distributed computation
10. Learning to predict by the methods of temporal differences

Their papers

• Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces (2014) — 73 citations
• Basis Adaptation for Sparse Nonlinear Reinforcement Learning (2013) — 11 citations