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142
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CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
16 years 9 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
150
Voted
WMCSA
2008
IEEE
15 years 9 months ago
HealthSense: classification of health-related sensor data through user-assisted machine learning
Remote patient monitoring generates much more data than healthcare professionals are able to manually interpret. Automated detection of events of interest is therefore critical so...
Erich P. Stuntebeck, John S. Davis II, Gregory D. ...
106
Voted
ICALT
2005
IEEE
15 years 8 months ago
MALESAbrain for Problem-Based Learning in IT Education
This paper reports MALESAbrain an intelligent online tool for problem-based learning (PBL) in IT education. The learning model of MALESAbrain is built on the notions of threshold ...
Akcell Chiang, Mohd Sapiyan Baba

Book
778views
17 years 22 days 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...
CLUSTER
2007
IEEE
15 years 6 months ago
Identifying energy-efficient concurrency levels using machine learning
Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessor...
Matthew Curtis-Maury, Karan Singh, Sally A. McKee,...