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» Coping With Uncertainty in Map Learning
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CIKM
2005
Springer
13 years 11 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia
AMS
2007
Springer
288views Robotics» more  AMS 2007»
13 years 12 months ago
Autonomous Exploration for 3D Map Learning
Abstract. Autonomous exploration is a frequently addressed problem in the robotics community. This paper presents an approach to mobile robot exploration that takes into account th...
Dominik Joho, Cyrill Stachniss, Patrick Pfaff, Wol...
ASP
2003
Springer
13 years 11 months ago
Mappings Between Domain Models in Answer Set Programming
Integration of data is required when accessing multiple databases within an organization or on the WWW. Schema integration is required for database interoperability, but it is curr...
Stefania Costantini, Andrea Formisano, Eugenio G. ...
CORR
2006
Springer
99views Education» more  CORR 2006»
13 years 5 months ago
Logical settings for concept learning from incomplete examples in First Order Logic
We investigate here concept learning from incomplete examples. Our first purpose is to discuss to what extent logical learning settings have to be modified in order to cope with da...
Dominique Bouthinon, Henry Soldano, Véroniq...
ICCV
2011
IEEE
12 years 5 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille