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» A Randomized Method for Integrated Exploration
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ICML
2007
IEEE
15 years 10 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
JMLR
2010
145views more  JMLR 2010»
14 years 4 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
ECCV
2008
Springer
15 years 11 months ago
Object Recognition by Integrating Multiple Image Segmentations
The joint tasks of object recognition and object segmentation from a single image are complex in their requirement of not only correct classification, but also deciding exactly whi...
Caroline Pantofaru, Cordelia Schmid, Martial Heber...
BMCBI
2010
193views more  BMCBI 2010»
14 years 4 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt
78
Voted
RAS
2006
123views more  RAS 2006»
14 years 9 months ago
Planning exploration strategies for simultaneous localization and mapping
In this paper, we present techniques that allow one or multiple mobile robots to efficiently explore and model their environment. While much existing research in the area of Simul...
Benjamín Tovar, Lourdes Muñoz-G&oacu...