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CVPR
2012
IEEE
13 years 23 hour ago
Geometry constrained sparse coding for single image super-resolution
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
Xiaoqiang Lu, Haoliang Yuan, Pingkun Yan, Yuan Yua...
ICML
2001
IEEE
15 years 10 months ago
Constrained K-means Clustering with Background Knowledge
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...
CVPR
2005
IEEE
15 years 11 months ago
Learning Appearance Manifolds from Video
The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this lowdimensional rep...
Ali Rahimi, Ben Recht, Trevor Darrell
TROB
2008
207views more  TROB 2008»
14 years 9 months ago
Learning Object Affordances: From Sensory-Motor Coordination to Imitation
Affordances encode relationships between actions, objects and effects. They play an important role on basic cognitive capabilities such as prediction and planning. We address the p...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
KCAP
2009
ACM
15 years 4 months ago
POIROT: acquiring workflows by combining models learned from interpreted traces
The POIROT project is a four-year effort to develop an architecture that integrates the products of a number of targeted reasoning and learning components to produce executable re...
Mark H. Burstein, Fusun Yaman, Robert Laddaga, Rob...