Two formalisms, both based on context-free grammars, have recently been proposed as a basis for a non-uniform random generation of combinatorial objects. The former, introduced by Denise et al, associates weights with letters, while the latter, recently explored by Weinberg et al in the context of random generation, associates weights to transitions. In this short note, we use a simple modification of the Greibach Normal Form transformation algorithm, due to Blum and Koch, to show the equivalent expressivities, in term of their induced distributions, of these two formalisms
In this paper, we consider probabilistic context-free grammars, a class of generative devices that h...
In this paper, we consider probabilistic context-free grammars, a class of generative devices that h...
We examine the expressive power of probabilistic context free grammars (PCFGs), with a special focus...
Two formalisms, both based on context-free grammars, have recently been proposed as a basis for a no...
This article studies the relationship between weighted context-free grammars (WCFGs), where each pro...
Devices for the generation of languages, corresponding to the probabilistic recognition devices or p...
It is proved that for a probabilistic context-free language L(G), the population density of a charac...
We present an algorithm which given an arbitrary A-free context-free grammar produces an equivalent ...
International audienceThe present work analyzes the redundancy of sets of combinatorial objects prod...
AbstractContext-free grammars are widely used for the simple form of their rules. A derivation step ...
The problem of identifying a probabilistic context free grammar has two aspects: the first is determ...
We consider languages generated by weighted context-free grammars. It is shown that the behaviour of...
We develop a new method for placing a given context-free grammar into Greibach normal form with onl...
We prove an analog of Parikh's theorem for weighted context-free grammars over commutative, idempot...
Parikh\u27s Theorem states that every context-free grammar (CFG) is equivalent to some regular CFG w...
In this paper, we consider probabilistic context-free grammars, a class of generative devices that h...
In this paper, we consider probabilistic context-free grammars, a class of generative devices that h...
We examine the expressive power of probabilistic context free grammars (PCFGs), with a special focus...
Two formalisms, both based on context-free grammars, have recently been proposed as a basis for a no...
This article studies the relationship between weighted context-free grammars (WCFGs), where each pro...
Devices for the generation of languages, corresponding to the probabilistic recognition devices or p...
It is proved that for a probabilistic context-free language L(G), the population density of a charac...
We present an algorithm which given an arbitrary A-free context-free grammar produces an equivalent ...
International audienceThe present work analyzes the redundancy of sets of combinatorial objects prod...
AbstractContext-free grammars are widely used for the simple form of their rules. A derivation step ...
The problem of identifying a probabilistic context free grammar has two aspects: the first is determ...
We consider languages generated by weighted context-free grammars. It is shown that the behaviour of...
We develop a new method for placing a given context-free grammar into Greibach normal form with onl...
We prove an analog of Parikh's theorem for weighted context-free grammars over commutative, idempot...
Parikh\u27s Theorem states that every context-free grammar (CFG) is equivalent to some regular CFG w...
In this paper, we consider probabilistic context-free grammars, a class of generative devices that h...
In this paper, we consider probabilistic context-free grammars, a class of generative devices that h...
We examine the expressive power of probabilistic context free grammars (PCFGs), with a special focus...