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» Stochastic complexity in learning
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HIS
2007
14 years 11 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 3 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
14 years 11 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
14 years 11 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»
14 years 10 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