Adam White
Reinforcement Learning · 2006–2019
A researcher in the Science corpus: 14 papers; trusts 129 researchers and is trusted by 60 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 212 citations into it; #377 of 2,242 by trust here, #481 by citations
- Artificial Intelligence — 118 citations into it; #3,533 of 35,345 by trust here, #4,393 by citations
- Optimization & Training — 34 citations into it
- Management Science and Operations Research — 26 citations into it; #7,500 of 11,946 by trust here, #9,931 by citations
- Computational Theory and Mathematics — 22 citations into it; #8,448 of 12,182 by trust here, #10,349 by citations
- Molecular Biology — 22 citations into it; #1,693 of 17,773 by trust here, #8,381 by citations
- Computer Vision and Pattern Recognition — 16 citations into it
- Control and Systems Engineering — 16 citations into it; #2,431 of 8,257 by trust here, #3,389 by citations
Whom Adam White trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Andrew Barto
- Justin A. Boyan
- Leemon C. Baird III
- Csaba Szepesvari
- Satinder Singh
- G. Tesauro
- Hamid Reza Maei
- J. Urgen Schmidhuber
- Doina Precup
Who trusts Adam White overall
- A. Mahmood
- Martha White
- Richard S. Sutton
- Yuxi Li
- Huizhen Yu
- Tom Schaul
- Shimon Whiteson
- W. B. Knox
- Peter Stone
- Vivek Veeriah
Papers from Adam White's perspective
Ordered by how strongly the researchers Adam White 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
- Reinforcement Learning: An Introduction
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction (2011) — 543 citations
- RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments (2009) — 129 citations
- Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains (2018) — 49 citations
- Multi-timescale nexting in a reinforcement learning robot (2011) — 133 citations
- The Reinforcement Learning Competitions (2010) — 47 citations
- The Barbados 2018 List of Open Issues in Continual Learning (2018) — 12 citations
- A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning (2016) — 51 citations
- Planning with Expectation Models (2019) — 26 citations
- Online Off-policy Prediction (2018) — 23 citations
- Investigating Practical Linear Temporal Difference Learning (2016) — 44 citations
- Reconstructing the basal angiosperm phylogeny: evaluating information content of mitochondrial genes (2006) — 116 citations
- DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE (2015) — 70 citations
- Surprise and Curiosity for Big Data Robotics (2014)
- Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains (2010) — 31 citations