This paper gives upper and lower bounds on the minimum error probability of Bayesian M -ary hypothesis testing in terms of the Arimoto-Rényi conditional entropy of an arbitrary order α. The improved tightness of these bounds over their specialized versions with the Shannon conditional entropy (α = 1) is demonstrated. In particular, in the case where M is finite, we show how to generalize Fano’s...

Randomness extraction against side information is the art of distilling from a given source a key which is almost uniform conditioned on the side information. This paper provides randomness extraction against quantum side information whose extractable key length is given by a quantum generalization of the conditional collision entropy defined without the conventional smoothing. Based on the fac...

Yager’s entropy was proposed to compute the information of fuzzy indiscernibility relation. In this paper we present a novel interpretation of Yager’s entropy in discernibility power of a relation point of view. Then some basic definitions in Shannon’s information theory are generalized based on Yager’s entropy. We introduce joint entropy, conditional entropy, mutual information and relative en...

Some concepts of information theory, as entropy, conditional entropy and mutual information may be very useful to analyse several financial time series, especially statistical dependences. Trough the similarity between those measures and variance analysis is possible to get a new approach to study the level of statistical dependences in financial time series. KEY-WORDS: entropy, conditional ent...

The notion of independence is of great importance in any formalism for managing uncertainty, for both theoretical and practical reasons. In this paper we study the concept of independence in the framework of possibility theory. Our approach to defining conditional independence relationships is based on comparing conditional possibility measures. Different comparison criteria are presented, base...

This paper puts forward a view on conditional commitments as causal rules, using action language K as the specification framework. The proposal builds upon an operational notion of social context, in such a way that conditional commitments are represented as rules in context. This approach enables the manipulation of conditional commitments in terms of the manipulation of the social interaction...

Relative observability has been introduced and studied in the framework of partially observed discrete-event systems as a condition stronger than observability, but weaker than normality. However, unlike observability, relative observability is closed under language unions, which makes it interesting for practical applications. In this paper, we investigate this notion in the framework of coord...

This paper presents our extractive summarization systems at the update summarization track of TAC 2009. This system is based on our newly developed document summarization framework under the theory of conditional information distance among many objects. The best summary is defined in this paper to be the one which has the minimum information distance to the entire document set. The best update ...

We propose a novel algorithm for extracting the structure of a Bayesian network from a dataset. Our approach is based on generalized conditional entropies, a parametric family of entropies that extends the usual Shannon conditional entropy. Our results indicate that with an appropriate choice of a generalized conditional entropy we obtain Bayesian networks that have superior scores compared to ...