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NECO
2007
127views more  NECO 2007»
13 years 7 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado

Book
778views
15 years 5 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
IEEEPACT
2008
IEEE
14 years 2 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
CF
2007
ACM
13 years 11 months ago
Fast compiler optimisation evaluation using code-feature based performance prediction
Performance tuning is an important and time consuming task which may have to be repeated for each new application and platform. Although iterative optimisation can automate this p...
Christophe Dubach, John Cavazos, Björn Franke...
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
13 years 8 months ago
Context-dependent predictions and cognitive arm control with XCSF
While John Holland has always envisioned learning classifier systems (LCSs) as cognitive systems, most work on LCSs has focused on classification, datamining, and function appro...
Martin V. Butz, Oliver Herbort