We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
Nowadays, automated Web document classification is considered as an important method to manage and process an enormous amount of Web documents in digital forms that are extensive a...
We evaluate three different relevance feedback (RF) algorithms, Rocchio, Robertson/Sparck-Jones (RSJ) and Bayesian, in the context of Web search. We use a target-testing experimen...
Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayli...
— In order to achieve reliable autonomous control in advanced robotic systems like entertainment robots, assistive robots, humanoid robots and autonomous vehicles, sensory data n...