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COLING
1996
13 years 9 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel
CORR
2007
Springer
112views Education» more  CORR 2007»
13 years 7 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky
STOC
1993
ACM
117views Algorithms» more  STOC 1993»
13 years 11 months ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns
AAAI
2010
13 years 9 months ago
Unsupervised Learning of Event Classes from Video
We present a method for unsupervised learning of event classes from videos in which multiple actions might occur simultaneously. It is assumed that all such activities are produce...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
BMCBI
2010
110views more  BMCBI 2010»
13 years 7 months ago
Discovering local patterns of co - evolution: computational aspects and biological examples
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Tamir Tuller, Yifat Felder, Martin Kupiec