This archive is provided as artifact material for the article "Learning Union of Integer Hypercubes with Queries (with applications to monadic decomposition)" Accepted for publication at CAV2021. Abstract: We study the problem of learning a finite union of integer (axis-aligned) hypercubes over the d-dimensional integer lattice, i.e., whose edges are parallel to the coordinate axes. This is a natural generalization of the classic problem in the computational learning theory of learning rectangles. We provide a learning algorithm with access to a minimally adequate teacher (i.e. membership and equivalence oracles) that solves this problem in polynomial-time, for any fixed dimension d. Over a non-fixed dimension, the problem subsumes the pro...
We introduce an abstract model of exact learning via queries that can be instantiated to all the q...
We present a new algorithm for a classic problem in computational geometry, Klee’s measure problem: ...
AbstractIn Valiant's protocol for learning, the classes of functions which are known learnable in po...
We present two algorithms that use membership and equivalence queries to exactly identify the concep...
We investigate the efficient learnability of unions of k rectangles in the discrete plane (1,...,n)[...
We consider the problem of learning unions of rectangles over the domain [b]n, in the uniform distri...
Abstract. We design efficient algorithms for on-line learning of axis-parallel rectangles (and for t...
AbstractWe consider the problem of learning unions of rectangles over the domain [b]n, in the unifor...
We first present an algorithm that uses membership and equivalence queries to exactly identify a di...
AbstractWe study the problem of properly learning unions of two axis-parallel rectangles over the do...
AbstractWe give the first polynomial time algorithm to learn any function of a constant number of ha...
1 Abstract We introduce an abstract model of exact learning via queries that can be instantiated to ...
AbstractThis paper investigates efficient learning of TPk, the class of collections of at most k fir...
We present exact learning algorithms that learn several classes of (discrete) boxes in f0; : : : ; `...
We give the first polynomial time algorithm to learn any function of a constant number of halfspaces...
We introduce an abstract model of exact learning via queries that can be instantiated to all the q...
We present a new algorithm for a classic problem in computational geometry, Klee’s measure problem: ...
AbstractIn Valiant's protocol for learning, the classes of functions which are known learnable in po...
We present two algorithms that use membership and equivalence queries to exactly identify the concep...
We investigate the efficient learnability of unions of k rectangles in the discrete plane (1,...,n)[...
We consider the problem of learning unions of rectangles over the domain [b]n, in the uniform distri...
Abstract. We design efficient algorithms for on-line learning of axis-parallel rectangles (and for t...
AbstractWe consider the problem of learning unions of rectangles over the domain [b]n, in the unifor...
We first present an algorithm that uses membership and equivalence queries to exactly identify a di...
AbstractWe study the problem of properly learning unions of two axis-parallel rectangles over the do...
AbstractWe give the first polynomial time algorithm to learn any function of a constant number of ha...
1 Abstract We introduce an abstract model of exact learning via queries that can be instantiated to ...
AbstractThis paper investigates efficient learning of TPk, the class of collections of at most k fir...
We present exact learning algorithms that learn several classes of (discrete) boxes in f0; : : : ; `...
We give the first polynomial time algorithm to learn any function of a constant number of halfspaces...
We introduce an abstract model of exact learning via queries that can be instantiated to all the q...
We present a new algorithm for a classic problem in computational geometry, Klee’s measure problem: ...
AbstractIn Valiant's protocol for learning, the classes of functions which are known learnable in po...