We address problems (that have since been addressed) in a proofs-version of a paper by Eva, Hartmann and Rad, who where attempting to justify the Kullback-Leibler divergence minimization solution to van Fraassen's Judy Benjamin problem
This paper addresses the problem of iterative optimization of the Kullback-Leibler (KL) divergence o...
In this paper, we provide a novel derivation of the probability hypothesis density (PHD) filter with...
International audienceWe consider a Kullback-Leibler-based algorithm for the stochastic multi-armed ...
We address problems with a recent attempt by Eva, Hartmann and Rad to justify the Kullback-Leibler d...
The problem of estimating the Kullback-Leibler divergence D(P||Q) between two unknown distributions ...
The goal of this short note is to discuss the relation between Kullback--Leibler divergence and tota...
Van Fraassen's Judy Benjamin problem has generally been taken to show that not all rational changes ...
The Kullback-Leibler (KL) divergence is a fundamental equation of information theory that quantifies...
The Jensen-Shannon divergence is a renown bounded symmetrization of the unbounded Kullback-Leibler d...
We provide optimal lower and upper bounds for the augmented Kullback-Leibler divergence in terms of ...
International audienceWe apply divergences to project a prior guess discrete probability law on pq e...
The Kullback-Leibler (KL) divergence is one of the most fundamental metrics in information theory an...
Kullback-Leibler divergence and the Neyman-Pearson lemma are two fundamental concepts in statistics....
To ensure stability of learning, state-of-the-art generalized policy iteration algorithms augment th...
Van Fraassen's Judy Benjamin problem asks how one ought to update one's credence in A upon receiving...
This paper addresses the problem of iterative optimization of the Kullback-Leibler (KL) divergence o...
In this paper, we provide a novel derivation of the probability hypothesis density (PHD) filter with...
International audienceWe consider a Kullback-Leibler-based algorithm for the stochastic multi-armed ...
We address problems with a recent attempt by Eva, Hartmann and Rad to justify the Kullback-Leibler d...
The problem of estimating the Kullback-Leibler divergence D(P||Q) between two unknown distributions ...
The goal of this short note is to discuss the relation between Kullback--Leibler divergence and tota...
Van Fraassen's Judy Benjamin problem has generally been taken to show that not all rational changes ...
The Kullback-Leibler (KL) divergence is a fundamental equation of information theory that quantifies...
The Jensen-Shannon divergence is a renown bounded symmetrization of the unbounded Kullback-Leibler d...
We provide optimal lower and upper bounds for the augmented Kullback-Leibler divergence in terms of ...
International audienceWe apply divergences to project a prior guess discrete probability law on pq e...
The Kullback-Leibler (KL) divergence is one of the most fundamental metrics in information theory an...
Kullback-Leibler divergence and the Neyman-Pearson lemma are two fundamental concepts in statistics....
To ensure stability of learning, state-of-the-art generalized policy iteration algorithms augment th...
Van Fraassen's Judy Benjamin problem asks how one ought to update one's credence in A upon receiving...
This paper addresses the problem of iterative optimization of the Kullback-Leibler (KL) divergence o...
In this paper, we provide a novel derivation of the probability hypothesis density (PHD) filter with...
International audienceWe consider a Kullback-Leibler-based algorithm for the stochastic multi-armed ...