Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
In this work, we quantitatively investigate the ways in which a given person influences the joint turn-taking behavior in a conversation. After collecting an auditory database of ...
Applications based on outsourcing computation require guarantees to the data owner that the desired computation has been performed correctly by the service provider. Methods based...
Optimized opportunistic multicast scheduling (OMS) has been studied previously by the authors for homogeneous cellular networks, where the problem of efficiently transmitting a co...
Tze-Ping Low, Man-On Pun, Yao-Win Peter Hong, C.-C...