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Decentralized learning enables a group of collaborative agents to learn models using a distributed dataset without the need for a central parameter server. Recently, decentralized learning algorithms have demonstrated state-of-the-art…

Machine Learning · Computer Science 2021-06-30 Yasaman Esfandiari , Sin Yong Tan , Zhanhong Jiang , Aditya Balu , Ethan Herron , Chinmay Hegde , Soumik Sarkar

We generalize the weighted cumulative entropies (WCRE and WCE), introduced in [5], for a system or component lifetime. Representing properties of cumulative entropies, several bounds and inequalities for the WCRE is proposed

Information Theory · Computer Science 2015-07-28 Yuri Suhov , Salimeh Yasaei Sekeh

To complete a previous work, the probability density functions for the errors in the center-of-gravity as positioning algorithm are derived with the usual methods of the cumulative distribution functions. These methods introduce substantial…

Instrumentation and Detectors · Physics 2021-03-08 Gregorio Landi , Giovanni E. Landi

Quantifying the directionality of information flow is instrumental in understanding, and possibly controlling, the operation of many complex systems, such as transportation, social, neural, or gene-regulatory networks. The standard Transfer…

Information Theory · Computer Science 2020-01-09 Jingjing Zhang , Osvaldo Simeone , Zoran Cvetkovic , Eugenio Abela , Mark Richardson

In this paper, we obtain a measure of inaccuracy between rth concomitant of generalized order statistic and the parent random variable in Morgenstern family. Applications of this result are given for concomitants of order statistics and…

Statistics Theory · Mathematics 2020-09-04 S. Daneshi , A. Nezakati , S. Tahmasebi , M. Longobardi

Probabilistic submeasures generalizing the classical (numerical) submeasures are introduced and discussed in connection with some classes of aggregation functions. A special attention is paid to triangular norm-based probabilistic…

Classical Analysis and ODEs · Mathematics 2012-07-12 Lenka Halčinová , Ondrej Hutník , Radko Mesiar

The main aim of this paper is twofold: (1) Suggesting a statistical mechanical approach to the calculation of the generating function of restricted integer partition functions which count the number of partitions --- a way of writing an…

Statistical Mechanics · Physics 2018-08-10 Chi-Chun Zhou , Wu-Sheng Dai

Performance analysis based on modelling consists of two major steps: model construction and model analysis. Formal modelling techniques significantly aid model construction but can exacerbate model analysis. In particular, here we consider…

Performance · Computer Science 2013-09-09 Alireza Pourranjbar , Jane Hillston

We consider estimation of the cumulative incidence function (CIF) in the competing risks Cox model. We study three methods. Methods 1 and 2 are existing methods while Method 3 is a newly-proposed method. Method 3 is constructed so that the…

Methodology · Statistics 2022-02-25 David M. Zucker , Malka Gorfine

There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as…

Information Theory · Computer Science 2011-11-29 David Balduzzi

In statistical physics, if we successively divide an equilibrium system into two parts, we will face a situation that, within a certain length $\xi$, the physics of a subsystem is no longer the same as the original system. Then the…

Quantum Physics · Physics 2009-11-13 Shi-Jian Gu , Chang-Pu Sun , Hai-Qing Lin

Cognitive structure is a student's subjective organization of an objective knowledge system, reflected in the psychological construction of concepts and their relations. However, cognitive structure assessment remains a long-standing…

Artificial Intelligence · Computer Science 2025-08-19 Hengnian Gu , Zhifu Chen , Yuxin Chen , Jin Peng Zhou , Dongdai Zhou

In this work, we establish a connection between the cumulative residual entropy and the Gini mean difference (GMD). Some relationships between the extropy and the GMD, and the truncated GMD and dynamic versions of the cumulative extropy are…

Statistics Theory · Mathematics 2022-08-29 Sudheesh Kattumannil , Sreedevi E. P , N. Balakrishnan

Categorical Gini Correlation (CGC), introduced by Dang et al. (2020), is a novel dependence measure designed to quantify the association between a numerical variable and a categorical variable. It has appealing properties compared to…

Methodology · Statistics 2026-05-12 Sameera Hewage

Randomness or mutual independence is an important underlying assumption for most widely used statistical methods for circular data. Verifying this assumption is essential to ensure the validity and reliability of the resulting inferences.…

Methodology · Statistics 2025-07-01 Shriya Gehlot , Arnab Kumar Laha

This paper presents a new recursive information consensus filter for decentralized dynamic-state estimation. No structure is assumed about the topology of the network and local estimators are assumed to have access only to local…

Systems and Control · Computer Science 2016-03-04 Amirhossein Tamjidi , Suman Chakravorty , Dylan Shell

Conditional generative models map input variables to complex, high-dimensional distributions, enabling realistic sample generation in a diverse set of domains. A critical challenge with these models is the absence of calibrated uncertainty,…

Machine Learning · Computer Science 2026-02-02 Qidong Yang , Qianyu Julie Zhu , Jonathan Giezendanner , Youssef Marzouk , Stephen Bates , Sherrie Wang

It is known that backward iterations of independent copies of a contractive random Lipschitz function converge almost surely under mild assumptions. By a sieving (or thinning) procedure based on adding to the functions time and space…

Probability · Mathematics 2020-03-25 Alexander Marynych , Ilya Molchanov

Contemporaneous aggregation of individual AR(1) random processes might lead to different properties of the limit aggregated time series, in particular, long memory (Granger, 1980). We provide a new characterization of the series of…

Statistics Theory · Mathematics 2015-08-11 Bernard Candelpergher , Michel Miniconi , Florian Pelgrin

This paper studies a training method to jointly estimate an energy-based model and a flow-based model, in which the two models are iteratively updated based on a shared adversarial value function. This joint training method has the…

Machine Learning · Statistics 2020-04-02 Ruiqi Gao , Erik Nijkamp , Diederik P. Kingma , Zhen Xu , Andrew M. Dai , Ying Nian Wu