Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
Spatial Pyramid Representation (SPR) is a widely used method for embedding both global and local spatial information into a feature, and it shows good performance in terms of gene...