This thesis deals with lower bounds for complexity measures related to subclasses of the class P of languages that can be decided by Turing machines in polynomial time. We consider non-uniform computational models like programs over monoids and branching programs.Our first contribution is an abstract, measure-independent treatment of Nečiporuk's method for proving lower bounds. This method still gives the best lower bounds known on measures such as the size of deterministic and non-deterministic branching programs or formulae{} with arbitrary binary Boolean operators; we give an abstract formulation of the method and use this framework to prove limits on the best lower bounds obtainable using this method for several complexity measures. We ...
AbstractWe consider a model of computation where the execution of a program on an input corresponds ...
We study the problem of learning an unknown function represented as an expression or a program over ...
AbstractWe study the problem of learning an unknown function represented as an expression or a progr...
Cette thèse porte sur des minorants pour des mesures de complexité liées à des sous-classes de la cl...
Cette thèse porte sur des minorants pour des mesures de complexité liées à des sous-classes de la cl...
International audienceThe program-over-monoid model of computation originates with Barrington's proo...
International audienceThe program-over-monoid model of computation originates with Barrington's proo...
International audienceThe model of programs over (finite) monoids, introduced by Barrington and Thér...
The program-over-monoid model of computation originates with Barrington's proof that the model captu...
International audienceThe program-over-monoid model of computation originates with Barrington's proo...
AbstractWe study the regular languages recognized by polynomial-length programs over finite semigrou...
AbstractIt is well known that varieties of rational languages are in one-to-one correspondence with ...
International audienceThe model of programs over (finite) monoids, introduced by Barrington and Thér...
In this thesis, we address a number of issues pertaining to the computational power of monoids and ...
AbstractBarrington's “polynomal-length program over a monoid” is a model of computation which has be...
AbstractWe consider a model of computation where the execution of a program on an input corresponds ...
We study the problem of learning an unknown function represented as an expression or a program over ...
AbstractWe study the problem of learning an unknown function represented as an expression or a progr...
Cette thèse porte sur des minorants pour des mesures de complexité liées à des sous-classes de la cl...
Cette thèse porte sur des minorants pour des mesures de complexité liées à des sous-classes de la cl...
International audienceThe program-over-monoid model of computation originates with Barrington's proo...
International audienceThe program-over-monoid model of computation originates with Barrington's proo...
International audienceThe model of programs over (finite) monoids, introduced by Barrington and Thér...
The program-over-monoid model of computation originates with Barrington's proof that the model captu...
International audienceThe program-over-monoid model of computation originates with Barrington's proo...
AbstractWe study the regular languages recognized by polynomial-length programs over finite semigrou...
AbstractIt is well known that varieties of rational languages are in one-to-one correspondence with ...
International audienceThe model of programs over (finite) monoids, introduced by Barrington and Thér...
In this thesis, we address a number of issues pertaining to the computational power of monoids and ...
AbstractBarrington's “polynomal-length program over a monoid” is a model of computation which has be...
AbstractWe consider a model of computation where the execution of a program on an input corresponds ...
We study the problem of learning an unknown function represented as an expression or a program over ...
AbstractWe study the problem of learning an unknown function represented as an expression or a progr...