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» Learning hierarchical task networks by observation
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PKDD
2009
Springer
174views Data Mining» more  PKDD 2009»
14 years 2 months ago
Active and Semi-supervised Data Domain Description
Data domain description techniques aim at deriving concise descriptions of objects belonging to a category of interest. For instance, the support vector domain description (SVDD) l...
Nico Görnitz, Marius Kloft, Ulf Brefeld
JMLR
2008
141views more  JMLR 2008»
13 years 7 months ago
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...
ICPR
2010
IEEE
13 years 10 months ago
The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking
This work introduces a new pattern recognition model for segmenting and tracking lip contours in video sequences. We formulate the problem as a general nonrigid object tracking me...
Gustavo Carneiro, Jacinto Nascimento
ABIALS
2008
Springer
14 years 1 months ago
A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies
Anticipation and prediction have been identified as key functions of many brain areas facilitating recognition, perception, and planning. In this chapter we present a hierarchical ...
Anthony F. Morse, Robert Lowe, Tom Ziemke
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 10 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...