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101
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NIPS
2007
15 years 2 months ago
Variational inference for Markov jump processes
Markov jump processes play an important role in a large number of application domains. However, realistic systems are analytically intractable and they have traditionally been ana...
Manfred Opper, Guido Sanguinetti
UAI
2003
15 years 2 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
118
Voted
ICONIP
2007
15 years 2 months ago
Natural Conjugate Gradient in Variational Inference
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
117
Voted
ISIPTA
2005
IEEE
168views Mathematics» more  ISIPTA 2005»
15 years 6 months ago
Approximate Inference in Credal Networks by Variational Mean Field Methods
Graph-theoretical representations for sets of probability measures (credal networks) generally display high complexity, and approximate inference seems to be a natural solution fo...
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
ICCAD
2005
IEEE
97views Hardware» more  ICCAD 2005»
15 years 9 months ago
DiCER: distributed and cost-effective redundancy for variation tolerance
— Increasingly prominent variational effects impose imminent threat to the progress of VLSI technology. This work explores redundancy, which is a well-known fault tolerance techn...
Di Wu, Ganesh Venkataraman, Jiang Hu, Quiyang Li, ...