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UAI
1996
15 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
FAC
2008
100views more  FAC 2008»
15 years 7 months ago
Slicing communicating automata specifications: polynomial algorithms for model reduction
Abstract. Slicing is a program analysis technique that was originally introduced to improve program debugging and understanding. The purpose of a slicing algorithm is to remove the...
Sébastien Labbé, Jean-Pierre Gallois
TASLP
2008
98views more  TASLP 2008»
15 years 6 months ago
Unsupervised Single-Channel Music Source Separation by Average Harmonic Structure Modeling
Source separation of musical signals is an appealing but difficult problem, especially in the single-channel case. In this paper, an unsupervised single-channel music source separa...
Zhiyao Duan, Yungang Zhang, Changshui Zhang, Zhenw...
IDT
2010
124views more  IDT 2010»
15 years 5 months ago
Modelling decision making with probabilistic causation
Humans know how to reason based on cause and effect, but cause and effect is not enough to draw conclusions due to the problem of imperfect information and uncertainty. To resol...
Luís Moniz Pereira, Carroline Kencana Ramli
EMNLP
2010
15 years 5 months ago
Training Continuous Space Language Models: Some Practical Issues
Using multi-layer neural networks to estimate the probabilities of word sequences is a promising research area in statistical language modeling, with applications in speech recogn...
Hai Son Le, Alexandre Allauzen, Guillaume Wisniews...