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» Computational Techniques for Modelling Learning in Economics
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PAMI
2008
161views more  PAMI 2008»
14 years 9 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
PASTE
2010
ACM
15 years 2 months ago
Learning universal probabilistic models for fault localization
Recently there has been significant interest in employing probabilistic techniques for fault localization. Using dynamic dependence information for multiple passing runs, learnin...
Min Feng, Rajiv Gupta
83
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ISWC
2003
IEEE
15 years 2 months ago
Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing
Context-aware computing describes the situation where a wearable / mobile computer is aware of its user’s state and surroundings and modifies its behavior based on this informat...
Andreas Krause, Daniel P. Siewiorek, Asim Smailagi...
IJCAI
2007
14 years 11 months ago
Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis
Computing semantic relatedness of natural language texts requires access to vast amounts of common-sense and domain-specific world knowledge. We propose Explicit Semantic Analysi...
Evgeniy Gabrilovich, Shaul Markovitch
AAAI
2007
14 years 12 months ago
Learning Graphical Model Structure Using L1-Regularization Paths
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin ...