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» Learning Classes of Probabilistic Automata
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LWA
2004
13 years 8 months ago
Learning Prototype Ontologies by Hierachical Latent Semantic Analysis
An ontology is a speci...cation of a conceptualization, a shared understanding of some domain of interest. The paper develops an algorithm that hierarchically groups words together...
Gerhard Paaß, Jörg Kindermann, Edda Leo...
NIPS
2008
13 years 8 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
IROS
2006
IEEE
132views Robotics» more  IROS 2006»
14 years 1 months ago
Supervised Learning of Topological Maps using Semantic Information Extracted from Range Data
Abstract— This paper presents an approach to create topological maps from geometric maps obtained with a mobile robot in an indoor-environment using range data. Our approach util...
Óscar Martínez Mozos, Wolfram Burgar...
ICML
2010
IEEE
13 years 5 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
UAI
1997
13 years 8 months ago
Exploring Parallelism in Learning Belief Networks
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Tongsheng Chu, Yang Xiang