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17 years 4 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...
WWW
2008
ACM
16 years 7 months ago
Why web 2.0 is good for learning and for research: principles and prototypes
The term "Web 2.0" is used to describe applications that distinguish themselves from previous generations of software by a number of principles. Existing work shows that...
Carsten Ullrich, Kerstin Borau, Heng Luo, Xiaohong...
IBPRIA
2009
Springer
15 years 11 months ago
Large Scale Online Learning of Image Similarity through Ranking
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
NIPS
1994
15 years 7 months ago
Catastrophic Interference in Human Motor Learning
Biological sensorimotor systems are not static maps that transform input sensory information into output motor behavior. Evidence from many lines of research suggests that their r...
Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov
TWC
2008
120views more  TWC 2008»
15 years 6 months ago
Cooperation Enforcement and Learning for Optimizing Packet Forwarding in Autonomous Wireless Networks
In wireless ad hoc networks, autonomous nodes are reluctant to forward others' packets because of the nodes' limited energy. However, such selfishness and noncooperation ...
Charles Pandana, Zhu Han, K. J. Ray Liu