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ICPR
2002
IEEE
16 years 7 months ago
Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection
Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...
IJCNN
2006
IEEE
16 years 17 days ago
Bi-directional Modularity to Learn Visual Servoing Tasks
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...
Gilles Hermann, Patrice Wira, Jean-Philippe Urban
COLT
2001
Springer
15 years 11 months ago
Smooth Boosting and Learning with Malicious Noise
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
Rocco A. Servedio
CE
2006
161views more  CE 2006»
15 years 6 months ago
Applying an authentic, dynamic learning environment in real world business
This paper describes a dynamic computer-based business learning environment and the results from applying it in a real-world business organization. We argue for using learning too...
Timo Lainema, Sami Nurmi
STOC
2004
ACM
102views Algorithms» more  STOC 2004»
16 years 6 months ago
A simple polynomial-time rescaling algorithm for solving linear programs
The perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for le...
John Dunagan, Santosh Vempala