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ML
2002
ACM
13 years 8 months ago
2002
ACM
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
SAC
2006
ACM
13 years 9 months ago
2006
ACM
Fast and accurate fault detection is becoming an essential component of management software for mission critical systems. A good fault detector makes possible to initiate repair a...
CORR
2010
Springer
13 years 9 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
PREMI
2007
Springer
14 years 3 months ago
2007
Springer
Abstract. This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We ar...
NIPS
1996
13 years 10 months ago
1996
This paper compares three penalty terms with respect to the efficiency of supervised learning, by using first- and second-order learning algorithms. Our experiments showed that fo...