Richard Maclin
Model Architectures · 1992–2005
A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Model Architectures — 10 citations into it
- Reinforcement Learning — 5 citations into it
- Representation & Self-Supervised Learning — 5 citations into it
Whom Richard Maclin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert E. Schapire
- David E. Rumelhart
- Geoffrey E. Hinton
- J. Ross Quinlan
- Leo Breiman
- Jerome H. Friedman
- David Hilton Wolpert
- Richard S. Sutton
- Yoav Freund
- Scott E. Fahlman
Who trusts Richard Maclin overall
- Johannes Fürnkranz
- K. Smith‐Miles
- S. Kotsiantis
- Prem Melville
- Zhi-Hua Zhou
- J. Urgen Schmidhuber
- J. Kolter
- Duc Le
- Byron Knoll
- Erik P. Garrison
Papers from Richard Maclin's perspective
Ordered by how strongly the researchers Richard Maclin 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Reinforcement Learning: An Introduction
Their papers
- Giving Advice about Preferred Actions to Reinforcement Learners Via Knowledge-Based Kernel Regression (2005) — 107 citations
- Popular Ensemble Methods: An Empirical Study (1999)
- Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks (1995)
- Using knowledge-based neural networks to improve algorithms: Refining the Chou-Fasman algorithm for protein folding (1992)