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» Stochastic complexity in learning
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HIS
2007
15 years 5 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
EMMCVPR
2005
Springer
15 years 9 months ago
Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
BIOCOMP
2007
15 years 5 months ago
Interaction Models for Biochemical Reactions
Abstract—This paper presents a stochastic modelling framework for complex biochemical reaction networks from a component-based perspective. Our approach takes into account the di...
Mila E. Majster-Cederbaum, Nils Semmelrock, Verena...
UAI
2008
15 years 5 months ago
Church: a language for generative models
Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...
ENTCS
2006
155views more  ENTCS 2006»
15 years 3 months ago
Biomolecular Agents as Multi-behavioural Concurrent Objects
In recent years, there has been increasing interest in computational models of biological systems based on various calculi of communicating processes, such as the stochastic pi-ca...
Denys Duchier, Céline Kuttler