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» Modeling affordances using Bayesian networks
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PAMI
2011
14 years 4 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
89
Voted
ISMB
2004
14 years 11 months ago
Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data
Motivation: Sigma factors regulate the expression of genes in Bacillus subtilis at the transcriptional level. First we assess the ability of currently available gene regulatory ne...
Michiel J. L. de Hoon, Yuko Makita, Seiya Imoto, K...
AAAI
2000
14 years 11 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
87
Voted
IWANN
2009
Springer
15 years 2 months ago
Easing the Smart Home: Translating Human Hierarchies to Intelligent Environments
Abstract. Ubiquitous computing research have extended traditional environments in the so–called Intelligent Environments. All of them use their capabilities for pursuing their in...
Manuel García-Herranz, Pablo A. Haya, Xavie...
AI
2010
Springer
14 years 9 months ago
Soft arc consistency revisited
The Valued Constraint Satisfaction Problem (VCSP) is a generic optimization problem defined by a network of local cost functions defined over discrete variables. It has applicatio...
Martin C. Cooper, Simon de Givry, M. Sanchez, Thom...