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» Dominating Distributions and Learnability
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ICML
1999
IEEE
14 years 10 months ago
Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
Rajesh Parekh, Vasant Honavar
AI
2010
Springer
13 years 10 months ago
Learning conditional preference networks
We investigate the problem of eliciting CP-nets in the well-known model of exact learning with equivalence and membership queries. The goal is to identify a preference ordering wi...
Frédéric Koriche, Bruno Zanuttini
COLT
1995
Springer
14 years 1 months ago
On the Learnability and Usage of Acyclic Probabilistic Finite Automata
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Dana Ron, Yoram Singer, Naftali Tishby
ICML
1996
IEEE
14 years 10 months ago
On the Learnability of the Uncomputable
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...
Richard H. Lathrop
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
14 years 1 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski