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PRL
2010
149views more  PRL 2010»
14 years 10 months ago
Adaptive linear models for regression: Improving prediction when population has changed
The general setting of regression analysis is to identify a relationship between a response variable Y and one or several explanatory variables X by using a learning sample. In a ...
Charles Bouveyron, Julien Jacques
CIKM
2011
Springer
14 years 3 months ago
Focusing on novelty: a crawling strategy to build diverse language models
Word prediction performed by language models has an important role in many tasks as e.g. word sense disambiguation, speech recognition, hand-writing recognition, query spelling an...
Luciano Barbosa, Srinivas Bangalore
AAAI
2007
15 years 5 months ago
An Investigation into Computational Recognition of Children's Jokes
bstract or nonliving entities act or are described as living. And living things gain extra benefits such as animals talking. For this reason, the standard scripts are modified to a...
Julia M. Taylor, Lawrence J. Mazlack
ALT
2005
Springer
16 years 3 days ago
PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance
We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Nick Palmer, Paul W. Goldberg
AAAI
2008
15 years 5 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio