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ICML
2010
IEEE
13 years 8 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint
BMCBI
2010
147views more  BMCBI 2010»
13 years 7 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
NIPS
2000
13 years 8 months ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
ML
1998
ACM
220views Machine Learning» more  ML 1998»
13 years 7 months ago
Learning to Improve Coordinated Actions in Cooperative Distributed Problem-Solving Environments
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
Toshiharu Sugawara, Victor R. Lesser
BMCBI
2007
215views more  BMCBI 2007»
13 years 7 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer