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ICML
2007
IEEE
14 years 8 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin
AAAI
2011
12 years 7 months ago
Combining Learned Discrete and Continuous Action Models
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
Joseph Z. Xu, John E. Laird
CVPR
2008
IEEE
14 years 9 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
MICCAI
2010
Springer
13 years 6 months ago
Manifold Learning for Biomarker Discovery in MR Imaging
We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel...
GRAPHICSINTERFACE
2003
13 years 9 months ago
Learning from Games: HCI Design Innovations in Entertainment Software
Computer games are one of the most successful application domains in the history of interactive systems. This success has come despite the fact that games were ‘separated at bir...
Jeff Dyck, David Pinelle, Barry Brown, Carl Gutwin