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VLSID
2007
IEEE
97views VLSI» more  VLSID 2007»
14 years 1 months ago
Embedded Support Vector Machine : Architectural Enhancements and Evaluation
In recent years, research and development in the field of machine learning and classification techniques have gained paramount importance. The future generation of intelligent e...
Soumyajit Dey, Monu Kedia, Niket Agarwal, Anupam B...
NIPS
1998
13 years 8 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
ECTEL
2009
Springer
13 years 10 months ago
Remote Hands-On Experience: Distributed Collaboration with Augmented Reality
One claim of Technology-Enhanced Learning (TEL) is to support and exploit benefits from distance learning and remote collaboration. On the other hand, several approaches to learnin...
Matthias Krauß, Kai Riege, Marcus Winter, Ly...
CCR
2010
156views more  CCR 2010»
13 years 7 months ago
Evolvable network architectures: what can we learn from biology?
There is significant research interest recently to understand the evolution of the current Internet, as well as to design clean-slate Future Internet architectures. Clearly, even ...
Constantine Dovrolis, J. Todd Streelman
SOFSEM
2010
Springer
14 years 4 months ago
Regret Minimization and Job Scheduling
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Yishay Mansour