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ESOP
2011
Springer
12 years 11 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...
KDD
2002
ACM
136views Data Mining» more  KDD 2002»
14 years 8 months ago
Relational Markov models and their application to adaptive web navigation
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
Corin R. Anderson, Pedro Domingos, Daniel S. Weld
PAMI
2007
166views more  PAMI 2007»
13 years 7 months ago
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
—This paper presents a novel probabilistic approach to hierarchical, exemplar-based shape matching. No feature correspondence is needed among exemplars, just a suitable pairwise ...
Dariu Gavrila
MABS
2000
Springer
13 years 11 months ago
Multi Agent Based Simulation: Beyond Social Simulation
Multi Agent Based Simulation (MABS) has been used mostly in purely social contexts. However, compared to other approaches, e.g., traditional discrete event simulation, object-orien...
Paul Davidsson
NIPS
2003
13 years 8 months ago
Envelope-based Planning in Relational MDPs
A mobile robot acting in the world is faced with a large amount of sensory data and uncertainty in its action outcomes. Indeed, almost all interesting sequential decision-making d...
Natalia Hernandez-Gardiol, Leslie Pack Kaelbling