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IJCAI
2001
15 years 3 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
118
Voted
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
15 years 3 months ago
Adapted Pittsburgh classifier system: building accurate strategies in non markovian environments
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments con...
Gilles Énée, Mathias Péroumal...
134
Voted
DAGM
2010
Springer
15 years 2 months ago
Semi-supervised Learning of Edge Filters for Volumetric Image Segmentation
Abstract. For every segmentation task, prior knowledge about the object that shall be segmented has to be incorporated. This is typically performed either automatically by using la...
Margret Keuper, Robert Bensch, Karsten Voigt, Alex...
147
Voted
COMCOM
2010
276views more  COMCOM 2010»
15 years 2 months ago
Adjustable convergecast tree protocol for wireless sensor networks
For data-collection applications in sensor networks, it is important to ensure base station receives a complete picture about the monitored area. Convergecast is an important commu...
Tzung-Shi Chen, Hua-Wen Tsai, Chih-Ping Chu
DAM
2006
132views more  DAM 2006»
15 years 2 months ago
On the combinatorial structure of chromatic scheduling polytopes
Chromatic scheduling polytopes arise as solution sets of the bandwidth allocation problem in certain radio access networks, supplyingwirelessaccesstovoice/datacommunicationnetwork...
Javier Marenco, Annegret Wagler