We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Library-based record and replay tools aim to reproduce an application's execution by recording the results of selected functions in a log and during replay returning the resu...
Zhenyu Guo, Xi Wang, Jian Tang, Xuezheng Liu, Zhil...
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
Gowers [Gow98, Gow01] introduced, for d 1, the notion of dimension-d uniformity Ud (f) of a function f : G C, where G is a finite abelian group. Roughly speaking, if a function ...
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...