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144
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ICML
2004
IEEE
16 years 4 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
180
Voted
FOIKS
2008
Springer
16 years 27 days ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
131
Voted
AUSAI
2005
Springer
15 years 9 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington
HICSS
2003
IEEE
95views Biometrics» more  HICSS 2003»
15 years 9 months ago
Matching Needs - Application Service Providing for Asynchronous Learning Networks
Universities have severe difficulties in using elearning applications successfully due to organizational problems to provide them. Providing a web-based learning environment is an...
Wolf-Gideon Bleek, Iver Jackewitz, Bernd Pape
ECAI
2006
Springer
15 years 7 months ago
Learning Behaviors Models for Robot Execution Control
Robust execution of robotic tasks is a difficult problem. In many situations, these tasks involve complex behaviors combining different functionalities (e.g. perception, localizat...
Guillaume Infantes, Félix Ingrand, Malik Gh...