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IJAR
2008
167views more  IJAR 2008»
15 years 6 months ago
Approximate algorithms for credal networks with binary variables
This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contai...
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
TIST
2011
136views more  TIST 2011»
15 years 1 months ago
Probabilistic models for concurrent chatting activity recognition
Recognition of chatting activities in social interactions is useful for constructing human social networks. However, the existence of multiple people involved in multiple dialogue...
Jane Yung-jen Hsu, Chia-chun Lian, Wan-rong Jih
ESOP
2011
Springer
14 years 10 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
GECCO
2004
Springer
132views Optimization» more  GECCO 2004»
16 years 1 days ago
Optimizing Topology and Parameters of Gene Regulatory Network Models from Time-Series Experiments
Abstract. In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. Different approaches to infer the dependencies of gene r...
Christian Spieth, Felix Streichert, Nora Speer, An...
JAIR
2006
137views more  JAIR 2006»
15 years 6 months ago
Learning Sentence-internal Temporal Relations
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
Maria Lapata, Alex Lascarides