We show that the class of all circuits is exactly learnable in randomized expected polynomial time using weak subset and weak superset queries. This is a consequence of the following result which we consider to be of independent interest: circuits are exactly learnable in randomized expected polynomial time with equivalence queries and the aid of an NP oracle. We also show that circuits are exactly learnable in deterministic polynomial time with equivalence queries and a Sigma-3 oracle. The paper also contains results on: learning of DNF formulas, learning with membership queries, and an application to Structural Complexity Theory
AbstractWe study the learnability of boolean functions from membership and equivalence queries. We d...
In a celebrated result Linial et al. [3] gave an algorithm which learns size-s depth-d AND/OR/NOT ci...
We prove several results giving new and stronger connections between learning theory, circuit comple...
We show that the class of all circuits is exactly learnable in randomized expected polynomial time u...
AbstractWe show that the class of all circuits is exactly learnable in randomized expected polynomia...
Circuit expressions were introduced to provide a natural link between Computational Learning and cer...
We investigate the query complexity of exact learning in the membership and (proper) equivalence que...
We study circuit expressions of logarithmic and poly-logarithmic polynomial-time Kolmogorov complexi...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2002.Includes bibliogr...
AbstractWe describe a new approach for understanding the difficulty of designing efficient learning ...
We show that Kolmogorov easy circuit expressions can be learned with membership queries in polynomia...
We study the learnability of boolean functions from membership and equivalence queries. We develop t...
We prove the following results. Any Boolean function of O(log n) relevant variables can be exactly ...
AbstractThe general dimension is a combinatorial measure that characterizes the number of queries ne...
We describe some recent or not-so-recent results in the model of learning known as exact learning f...
AbstractWe study the learnability of boolean functions from membership and equivalence queries. We d...
In a celebrated result Linial et al. [3] gave an algorithm which learns size-s depth-d AND/OR/NOT ci...
We prove several results giving new and stronger connections between learning theory, circuit comple...
We show that the class of all circuits is exactly learnable in randomized expected polynomial time u...
AbstractWe show that the class of all circuits is exactly learnable in randomized expected polynomia...
Circuit expressions were introduced to provide a natural link between Computational Learning and cer...
We investigate the query complexity of exact learning in the membership and (proper) equivalence que...
We study circuit expressions of logarithmic and poly-logarithmic polynomial-time Kolmogorov complexi...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2002.Includes bibliogr...
AbstractWe describe a new approach for understanding the difficulty of designing efficient learning ...
We show that Kolmogorov easy circuit expressions can be learned with membership queries in polynomia...
We study the learnability of boolean functions from membership and equivalence queries. We develop t...
We prove the following results. Any Boolean function of O(log n) relevant variables can be exactly ...
AbstractThe general dimension is a combinatorial measure that characterizes the number of queries ne...
We describe some recent or not-so-recent results in the model of learning known as exact learning f...
AbstractWe study the learnability of boolean functions from membership and equivalence queries. We d...
In a celebrated result Linial et al. [3] gave an algorithm which learns size-s depth-d AND/OR/NOT ci...
We prove several results giving new and stronger connections between learning theory, circuit comple...
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