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FLAIRS
2006
13 years 9 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
NIPS
1997
13 years 9 months ago
Nonparametric Model-Based Reinforcement Learning
This paper describes some of the interactions of model learning algorithms and planning algorithms we have found in exploring model-based reinforcement learning. The paper focuses...
Christopher G. Atkeson
CVPR
2009
IEEE
15 years 1 months ago
Learning Mixed Templates for Object Recognition
This article proposes a method for learning object templates composed of local sketches and local textures, and investigates the relative importance of the sketches and textures ...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...
IJCV
2008
266views more  IJCV 2008»
13 years 7 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han