Fusing partial estimates is a critical and common problem
in many computer vision tasks such as part-based detection
and tracking. It generally becomes complicated and
intractab...
Based on the observation that it is relatively easier for users to generate several good transfer functions (TFs) for different features of volumetric data, we propose TF fusing, ...
Yingcai Wu, Huamin Qu, Hong Zhou, Ming-Yuen Cha...
A key problem faced by classifiers is coping with styles not represented in the training set. We present an application of hierarchical Bayesian methods to the problem of recogniz...
We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...