To obtain classification systems with both good generalizat`ion performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers...
This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial...
We employed a white-noise velocity signal to study the dynamics of the response of single neurons in the cortical area MT to visual motion. Responses were quantified using reverse...
Wyeth Bair, James R. Cavanaugh, J. Anthony Movshon
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
Understanding knowledge representations in neural nets has been a difficult problem. Principal components analysis (PCA) of contributions (products of sending activations and conn...
Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Tak...
Experiments were performed to reveal some of the computational properties of the human motor memory system. We show that as humans practice reaching movements while interacting wi...
Reza Shadmehr, Tom Brashers-Krug, Ferdinando A. Mu...