Add to ORKGAbstract. This paper presents a new sequential algorithm to answer the question about the existence of a causal explanation for a set of independence statements (a dependency model), which is consistent with a given set of background knowledge. Emphasis is placed on generality, efficiency and ease of parallelization of the algorithm. From this sequential algorithm, an efficient, scalable, and easy to implement parallel algorithm with very little interprocessor communication is derived
International audienceIn distributed systems where strong consistency is costly when not impossible,...
Causality Checking [LL13a] has been proposed as a finite state space exploration technique which com...
We give a precise picture of the computational complexity of causal relationships in Pearl's structu...
Abstract. This paper presents a new sequential algorithm to answer the question about the existence ...
Inferring the causal structure that links n observables is usually based upon detecting statistical ...
In this paper, we establish a notion of causality that should be used as a desideratum for memory mo...
International audienceSeveral algorithms of different domains in distributed systems are designed ov...
We propose a framework for simple causal theories of action, and study the computational complexity ...
Causal modeling and the accompanying learning algorithms provide useful extensions for in-depth stat...
This paper reports experiments with the causal independence inference algorithm proposed by Zhang an...
International audienceThis paper presents a generalization of causal consistency suited to the famil...
In this paper we present an efficient causal multi-channel algorithm that can be used in a multigrou...
Contains fulltext : 91526.pdf (preprint version ) (Open Access)19th European Sympo...
International audienceWe compare three notions of knowledge in concurrent system: mem-oryless knowle...
Over the past twenty-five years, a large number of algorithms have been developed to learn the struc...
International audienceIn distributed systems where strong consistency is costly when not impossible,...
Causality Checking [LL13a] has been proposed as a finite state space exploration technique which com...
We give a precise picture of the computational complexity of causal relationships in Pearl's structu...
Abstract. This paper presents a new sequential algorithm to answer the question about the existence ...
Inferring the causal structure that links n observables is usually based upon detecting statistical ...
In this paper, we establish a notion of causality that should be used as a desideratum for memory mo...
International audienceSeveral algorithms of different domains in distributed systems are designed ov...
We propose a framework for simple causal theories of action, and study the computational complexity ...
Causal modeling and the accompanying learning algorithms provide useful extensions for in-depth stat...
This paper reports experiments with the causal independence inference algorithm proposed by Zhang an...
International audienceThis paper presents a generalization of causal consistency suited to the famil...
In this paper we present an efficient causal multi-channel algorithm that can be used in a multigrou...
Contains fulltext : 91526.pdf (preprint version ) (Open Access)19th European Sympo...
International audienceWe compare three notions of knowledge in concurrent system: mem-oryless knowle...
Over the past twenty-five years, a large number of algorithms have been developed to learn the struc...
International audienceIn distributed systems where strong consistency is costly when not impossible,...
Causality Checking [LL13a] has been proposed as a finite state space exploration technique which com...
We give a precise picture of the computational complexity of causal relationships in Pearl's structu...