A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
Abstract. In order to reconstruct 3-D Euclidean shape by the TomasiKanade factorization, one needs to specify an affine camera model such as orthographic, weak perspective, and par...
Ken-ichi Kanatani, Yasuyuki Sugaya, Hanno Ackerman...
Abstract. Sigmoidal or radial transfer functions do not guarantee the best generalization nor fast learning of neural networks. Families of parameterized transfer functions provide...
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
This paper presents a new computational framework for modelling visual-object based attention and attention-driven eye movements within an integrated system in a biologically insp...
Yaoru Sun, Robert B. Fisher, Fang Wang, Herman Mar...