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» Bayesian Unsupervised Learning of Higher Order Structure
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JETAI
1998
110views more  JETAI 1998»
13 years 7 months ago
Independency relationships and learning algorithms for singly connected networks
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
Luis M. de Campos
LREC
2010
149views Education» more  LREC 2010»
13 years 9 months ago
Paragraph Acquisition and Selection for List Question Using Amazon's Mechanical Turk
Creating more fine-grained annotated data than previously relevent document sets is important for evaluating individual components in automatic question answering systems. In this...
Fang Xu, Dietrich Klakow
HIS
2008
13 years 9 months ago
The Hybrid Integration of Perceptual Symbol Systems and Interactive Reinforcement Learning
In order to produce robots which can interact more effectively with humans we propose that it is necessary for their cognitive processes to be grounded in the same perceptual elem...
Michael John Knowles, Stefan Wermter
ALIFE
2010
13 years 6 months ago
Modeling Social Learning of Language and Skills
We present a model of social learning of both language and skills, while assuming—insofar as possible—strict autonomy, virtual embodiment, and situatedness. This model is built...
Paul Vogt, Evert Haasdijk
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 14 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer