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» Bayesian learning of measurement and structural models
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UAI
2008
13 years 11 months ago
Observation Subset Selection as Local Compilation of Performance Profiles
Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
Yan Radovilsky, Solomon Eyal Shimony
ESWS
2008
Springer
13 years 12 months ago
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
Christoph Kiefer, Abraham Bernstein, André ...
IJCAI
2007
13 years 11 months ago
Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition
Most existing sketch understanding systems require a closed domain to achieve recognition. This paper describes an incremental learning technique for opendomain recognition. Our s...
Andrew M. Lovett, Morteza Dehghani, Kenneth D. For...
TSP
2011
197views more  TSP 2011»
13 years 5 months ago
Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
—This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...
IROS
2009
IEEE
139views Robotics» more  IROS 2009»
14 years 4 months ago
Improving robot navigation in structured outdoor environments by identifying vegetation from laser data
— This paper addresses the problem of vegetation detection from laser measurements. The ability to detect vegetation is important for robots operating outdoors, since it enables ...
Kai M. Wurm, Rainer Kümmerle, Cyrill Stachnis...