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AAAI
2007
15 years 3 months ago
Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...
123
Voted
ICASSP
2010
IEEE
15 years 28 days ago
Structuring a gene network using a multiresolution independence test
In order to structure a gene network, a score-based approach is often used. A score-based approach, however, is problematic because by assuming a probability distribution, one is ...
Takayuki Yamamoto, Tetsuya Takiguchi, Yasuo Ariki
ISM
2008
IEEE
159views Multimedia» more  ISM 2008»
15 years 21 days ago
Adaptive Modeling of a User's Daily Life with a Wearable Sensor Network
In an environment where the contexts of users are complex and the degree of freedom of user activity is very high, such as in daily life, several factors need to be considered for...
Hyoungnyoun Kim, Ig-Jae Kim, Hyoung-Gon Kim, Ji-Hy...
112
Voted
FUZZIEEE
2007
IEEE
15 years 7 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
108
Voted
JAIR
2008
138views more  JAIR 2008»
15 years 21 days ago
Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and Decision-Making Processes
This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents' beliefs and decision-making processes....
Ya'akov Gal, Avi Pfeffer