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TSP
2010
13 years 3 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
CVPR
2012
IEEE
11 years 11 months ago
RGB-(D) scene labeling: Features and algorithms
Scene labeling research has mostly focused on outdoor scenes, leaving the harder case of indoor scenes poorly understood. Microsoft Kinect dramatically changed the landscape, show...
Xiaofeng Ren, Liefeng Bo, Dieter Fox
NIPS
2001
13 years 10 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning
ICCV
2009
IEEE
15 years 1 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICML
2006
IEEE
14 years 9 months ago
Bayesian pattern ranking for move prediction in the game of Go
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...
David H. Stern, Ralf Herbrich, Thore Graepel