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CVPR
2012
IEEE
11 years 10 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
MLG
2007
Springer
14 years 1 months ago
Learning Graph Matching
As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as gr...
Alex J. Smola
CSE
2009
IEEE
14 years 2 months ago
The Social Behaviors of Experts in Massive Multiplayer Online Role-Playing Games
— We examine the social behaviors of game experts in Everquest II, a popular massive multiplayer online role-playing game (MMO). We rely on Exponential Random Graph Models (ERGM)...
David Huffaker, Jing (Annie) Wang, Jeffrey William...
COLT
2010
Springer
13 years 5 months ago
Learning with Global Cost in Stochastic Environments
We consider an online learning setting where at each time step the decision maker has to choose how to distribute the future loss between k alternatives, and then observes the los...
Eyal Even-Dar, Shie Mannor, Yishay Mansour
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 6 months ago
Laplacian Spectrum Learning
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Pannagadatta K. Shivaswamy, Tony Jebara