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ML
2008
ACM
150views Machine Learning» more  ML 2008»
15 years 2 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
ICIP
2006
IEEE
16 years 4 months ago
Knowledge-Based Supervised Learning Methods in a Classical Problem of Video Object Tracking
In this paper we present a new scheme for detection and tracking of specific objects in a knowledge-based framework. The scheme uses a supervised learning method: Support Vector M...
Lionel Carminati, Jenny Benois-Pineau, Christian J...
ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 2 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
CG
2008
Springer
15 years 4 months ago
Learning Positional Features for Annotating Chess Games: A Case Study
Abstract. By developing an intelligent computer system that will provide commentary of chess moves in a comprehensible, user-friendly and instructive way, we are trying to use the ...
Matej Guid, Martin Mozina, Jana Krivec, Aleksander...
CVPR
2009
IEEE
16 years 10 months ago
Learning Shape Prior Models for Object Matching
The aim of this work is to learn a shape prior model for an object class and to improve shape matching with the learned shape prior. Given images of example instances, we can le...
Cordelia Schmid, Frédéric Jurie, Tin...