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HYBRID
2000
Springer
15 years 7 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
IJCAI
1989
15 years 4 months ago
Selective Learning of Macro-operators with Perfect Causality
A macro-operator is an integrated operator consisting of plural primitive operators and enables a problem solver to solve more efficiently. However, if a learning system generates...
Seiji Yamada, Sabinro Tsuji
121
Voted
ICMLA
2009
15 years 1 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz
132
Voted
JMLR
2010
154views more  JMLR 2010»
14 years 10 months ago
Infinite Predictor Subspace Models for Multitask Learning
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
Piyush Rai, Hal Daumé III
123
Voted
ACCV
1998
Springer
15 years 7 months ago
Learning Multiscale Image Models of 2D Object Classes
This paper isconcerned with learning the canonical gray scalestructure of the images of a classof objects. Structure is defined in terms of the geometry and layout of salientimage...
Benoit Perrin, Narendra Ahuja, Narayan Srinivasa