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» Splitting of Learnable Classes
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100
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ECML
1993
Springer
15 years 5 months ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
124
Voted
ICALP
2001
Springer
15 years 5 months ago
Separating Quantum and Classical Learning
We consider a model of learning Boolean functions from quantum membership queries. This model was studied in [26], where it was shown that any class of Boolean functions which is i...
Rocco A. Servedio
126
Voted
ALT
1997
Springer
15 years 5 months ago
Learning DFA from Simple Examples
Efficient learning of DFA is a challenging research problem in grammatical inference. It is known that both exact and approximate (in the PAC sense) identifiability of DFA is har...
Rajesh Parekh, Vasant Honavar
110
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ICML
1999
IEEE
16 years 1 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
102
Voted
COLT
2005
Springer
15 years 6 months ago
Learnability of Bipartite Ranking Functions
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
Shivani Agarwal, Dan Roth