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ALT
1998
Springer
15 years 11 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...
COLT
1994
Springer
15 years 10 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
COLT
2006
Springer
15 years 10 months ago
Learning Rational Stochastic Languages
Given a finite set of words w1, . . . , wn independently drawn according to a fixed unknown distribution law P called a stochastic language, an usual goal in Grammatical Inference ...
François Denis, Yann Esposito, Amaury Habra...
ECAI
2006
Springer
15 years 10 months ago
Automatic Generation of Implied Constraints
Abstract. A well-known difficulty with solving Constraint Satisfaction Problems (CSPs) is that, while one formulation of a CSP may enable a solver to solve it quickly, a different ...
John Charnley, Simon Colton, Ian Miguel
EUROCOLT
1995
Springer
15 years 10 months ago
A decision-theoretic generalization of on-line learning and an application to boosting
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
Yoav Freund, Robert E. Schapire