Agents that operate in a multi-agent system can benefit significantly from adapting to other agents while interacting with them. This work presents a general architecture for a ...
Given a directed graph in which some of the nodes are labeled, we investigate the question of how to exploit the link structure of the graph to infer the labels of the remaining u...
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
abstraction and text mining methods to exploit the collected data. Furthermore, our visual discovery system D2MS allowed to actively and effectively working with physicians. Signi...
Tu Bao Ho, Saori Kawasaki, Katsuhiko Takabayashi, ...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...