We show that probabilistic computable functions, i.e., those functions outputting distributions and computed by probabilistic Turing machines, can be characterized by a natural generalization of Church and Kleene’s partial recursive functions. The obtained algebra, following Leivant, can be restricted so as to capture the notion of polytime sampleable distributions, a key concept in average-case complexity and cryptography
We give an adequate denotational semantics for languages with recursive higher-order types, continuo...
Abstract. A randomized encoding of a function f(x) is a randomized function f̂(x, r), such that the ...
A leading idea is to apply techniques from verification and programming theory to machine learning a...
We show that probabilistic computable functions, i.e., those functions outputting distributions and ...
Abstract: We study a time bounded variant of Kolmogorov complexity. This motion, together with unive...
The thesis applies the ICC tecniques to the probabilistic polinomial complexity classes in order to ...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
International audienceWe show that complexity analysis of probabilistic higher-order functional prog...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
In this work, we develop a randomized bounded arithmetic for probabilistic computation, following th...
Various types of probabilistic algorithms play an increasingly important role in computer science, e...
Probabilistic complexity classes, despite capturing the notion of feasibility, have escaped any trea...
This paper defines a new notion of bounded computable randomness for certainclasses of sub-computabl...
We give an adequate denotational semantics for languages with recursive higher-order types, continuo...
Abstract. A randomized encoding of a function f(x) is a randomized function f̂(x, r), such that the ...
A leading idea is to apply techniques from verification and programming theory to machine learning a...
We show that probabilistic computable functions, i.e., those functions outputting distributions and ...
Abstract: We study a time bounded variant of Kolmogorov complexity. This motion, together with unive...
The thesis applies the ICC tecniques to the probabilistic polinomial complexity classes in order to ...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
International audienceWe show that complexity analysis of probabilistic higher-order functional prog...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
In this work, we develop a randomized bounded arithmetic for probabilistic computation, following th...
Various types of probabilistic algorithms play an increasingly important role in computer science, e...
Probabilistic complexity classes, despite capturing the notion of feasibility, have escaped any trea...
This paper defines a new notion of bounded computable randomness for certainclasses of sub-computabl...
We give an adequate denotational semantics for languages with recursive higher-order types, continuo...
Abstract. A randomized encoding of a function f(x) is a randomized function f̂(x, r), such that the ...
A leading idea is to apply techniques from verification and programming theory to machine learning a...