Results 31 to 40 of about 389,136 (225)
On the Interventional Kullback-Leibler Divergence [PDF]
CLEaR, 2023 Modern machine learning approaches excel in static settings where a large amount of i.i.d. training data are available for a given task. In a dynamic environment, though, an intelligent agent needs to be able to transfer knowledge and re-use learned ...
J. Wildberger +3 more
semanticscholar +1 more source
On Voronoi Diagrams on the Information-Geometric Cauchy Manifolds
Entropy, 2020 We study the Voronoi diagrams of a finite set of Cauchy distributions and their dual complexes from the viewpoint of information geometry by considering the Fisher-Rao distance, the Kullback-Leibler divergence, the chi square divergence, and a flat ...
Frank Nielsen
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Kullback-Leibler Divergence and Mutual Information of Experiments in the Fuzzy Case
Axioms, 2017 The main aim of this contribution is to define the notions of Kullback-Leibler divergence and conditional mutual information in fuzzy probability spaces and to derive the basic properties of the suggested measures.
Dagmar Markechová
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Kullback–Leibler Divergence and Mutual Information of Partitions in Product MV Algebras
Entropy, 2017 The purpose of the paper is to introduce, using the known results concerning the entropy in product MV algebras, the concepts of mutual information and Kullback–Leibler divergence for the case of product MV algebras and examine algebraic properties of ...
Dagmar Markechová, Beloslav Riečan
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Monotonic decrease of the quantum nonadditive divergence by projective measurements [PDF]
, 2003 Nonadditive (nonextensive) generalization of the quantum Kullback-Leibler divergence, termed the quantum q-divergence, is shown not to increase by projective measurements in an elementary manner.Comment: 10 pages, no figures.
Abe +27 more
core +2 more sources
Time series irreversibility: a visibility graph approach [PDF]
, 2011 We propose a method to measure real-valued time series irreversibility which combines two differ- ent tools: the horizontal visibility algorithm and the Kullback-Leibler divergence.
A. Nuñez +33 more
core +3 more sources
Some bounds for skewed α-Jensen-Shannon divergence
Results in Applied Mathematics, 2019 Based on the skewed Kullback-Leibler divergence introduced in the natural language processing, we derive the upper and lower bounds on the skewed version of the Jensen-Shannon divergence and investigate properties of them.
Takuya Yamano
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FeDDkw – Federated Learning with Dynamic Kullback–Leibler-divergence Weight
ACM Transactions on Asian and Low-Resource Language Information Processing, 2023 Federated learning (FL) has emerged as a promising framework for collaborative machine learning. As one of the most well-known bottlenecks of FL, data heterogeneity, i.e., non-IID data, has seriously hampered the convergence rate and model accuracy of FL.
Boyuan Li, Shengbo Chen, K. Yu
semanticscholar +1 more source
Dynamic fine‐tuning layer selection using Kullback–Leibler divergence
Engineering Reports, 2023 The selection of layers in the transfer learning fine‐tuning process ensures a pre‐trained model's accuracy and adaptation in a new target domain. However, the selection process is still manual and without clearly defined criteria. If the wrong layers in
Raphael Ngigi Wanjiku +2 more
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Algorithms, 2022 The family of α-divergences including the oriented forward and reverse Kullback–Leibler divergences is often used in signal processing, pattern recognition, and machine learning, among others.
Frank Nielsen
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