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» Learning with Weighted Transducers
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COLT
2001
Springer
14 years 1 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
FLAIRS
2007
13 years 11 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
AI
2008
Springer
13 years 9 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...
BC
2005
71views more  BC 2005»
13 years 9 months ago
The spatiotemporal learning rule and its efficiency in separating spatiotemporal patterns
The hippocampus plays an important role in the course of establishing long-term memory, i.e., to make short-term memory of spatially and temporally associated input information. In...
M. Tsukada, X. Pan
TNN
1998
111views more  TNN 1998»
13 years 9 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos