Neville Mehta
Reinforcement Learning · 2008
A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 9 citations into it
Whom Neville Mehta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thomas G. Dietterich
- Anton Schwartz
- Yaxin Liu
- Peter Stone
- Ronald E. Parr
- Richard S. Sutton
- Stuart J. Russell
- Carlos Guestrin
- Pieter Abbeel
- Craig Boutilier
Who trusts Neville Mehta overall
- Alessandro Lazaric
- Bernhard Hengst
- Mohammad Ghavamzadeh
- Satinder Singh
- Mostafa Al-Emran
- Marcello Restelli
- Richard L. Lewis
- Matthew E. Taylor
- Emma Brunskill
Papers from Neville Mehta's perspective
Ordered by how strongly the researchers Neville Mehta trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Reinforcement Learning: An Introduction
- ImageNet: A large-scale hierarchical image database
- Apprenticeship learning via inverse reinforcement learning
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Transfer in variable-reward hierarchical reinforcement learning (2008) — 102 citations