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ESOP
2011
Springer
14 years 3 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»
16 years 6 days 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»
14 years 11 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
15 years 3 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
15 years 1 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