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Rejoinder of "Estimating the historical and future probabilities of large terrorist events" by Aaron Clauset and Ryan Woodard [arXiv:1209.0089].

Applications · Statistics 2014-01-13 Aaron Clauset , Ryan Woodard

Review article of various complexity measures of networks

Adaptation and Self-Organizing Systems · Physics 2014-02-13 Russell K. Standish

Quantum Arithmetic faces limitations such as noise and resource constraints in the current Noisy Intermediate Scale Quantum (NISQ) era quantum computers. We propose using Distributed Quantum Computing (DQC) to overcome these limitations by…

Quantum Physics · Physics 2024-06-11 Bhaskar Gaur , Travis S. Humble , Himanshu Thapliyal

Quantum machine learning models incorporating data re-uploading circuits have garnered significant attention due to their exceptional expressivity and trainability. However, their ability to generate accurate predictions on unseen data,…

Quantum Physics · Physics 2025-10-29 Xin Wang , Han-Xiao Tao , Re-Bing Wu

Embeddings are ubiquitous in machine learning, appearing in recommender systems, NLP, and many other applications. Researchers and developers often need to explore the properties of a specific embedding, and one way to analyze embeddings is…

We analyze a known version of the discrete Wigner function and some connections with Quantum Iterated Funcion Systems. This paper is a follow up of "A dynamical point of view of Quantum Information: entropy and pressure" by the same…

Quantum Physics · Physics 2011-08-23 A. Baraviera , C. F. Lardizabal , A. O. Lopes , M. Terra Cunha

Rejoinder to ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]

Statistics Theory · Mathematics 2007-06-13 P. Laurie Davies , Ursula Gather

In order to vary the arithmetic resource consumption of neural network applications at runtime, this work proposes the flexible reuse of approximate multipliers for neural network layer computations. We introduce a search algorithm that…

Machine Learning · Computer Science 2024-10-11 Elias Trommer , Bernd Waschneck , Akash Kumar

State estimation for discrete-time linear systems with quantized measurements is addressed. By exploiting the set-theoretic nature of the information provided by the quantizer, the problem is cast in the set membership estimation setting.…

Systems and Control · Electrical Eng. & Systems 2023-12-05 Marco Casini , Andrea Garulli , Antonio Vicino

Benchmarking quantum computers helps to quantify them and bringing the technology to the market. Various application-level metrics exist to benchmark a quantum device at an application level. This paper presents a revised holistic scoring…

Quantum Physics · Physics 2024-06-07 Koen J. Mesman , Ward van der Schoot , Matthias Möller , Niels M. P. Neumann

Estimation is a critical component of synchronization in wireless and signal processing systems. There is a rich body of work on estimator derivation, optimization, and statistical characterization from analytic system models which are used…

Machine Learning · Computer Science 2017-07-21 Timothy J. O'Shea , Kiran Karra , T. Charles Clancy

Measuring Mutual Information (MI) between high-dimensional, continuous, random variables from observed samples has wide theoretical and practical applications. Recent work, MINE (Belghazi et al. 2018), focused on estimating tight…

Machine Learning · Computer Science 2019-05-28 Xiao Lin , Indranil Sur , Samuel A. Nastase , Ajay Divakaran , Uri Hasson , Mohamed R. Amer

In this paper, some points to the convergence analysis performed in the paper [A new computing approach for power signal modeling using fractional adaptive algorithms, ISA Transactions 68 (2017) 189-202] are presented. It is highlighted…

Optimization and Control · Mathematics 2020-03-24 Abdul Wahab , Shujaat Khan , Farrukh Zeeshan Khan

Resilient state recovery of cyber-physical systems has attracted much research attention due to the unique challenges posed by the tight coupling between communication, computation, and the underlying physics of such systems. By modeling…

Optimization and Control · Mathematics 2025-07-31 Yu Zheng , Olugbenga Moses Anubi , Warren E. Dixon

Quantum re-uploading models have been extensively investigated as a form of machine learning within the context of variational quantum algorithms. Their trainability and expressivity are not yet fully understood and are critical to their…

Quantum Physics · Physics 2024-11-26 Alice Barthe , Adrián Pérez-Salinas

This is a response to the commentaries on "CoRR: A Computing Research Repository".

Digital Libraries · Computer Science 2007-05-23 Joseph Y. Halpern

Since the introduction of network psychometrics, several connections to statistical models in "classical" psychometrics (i.e., IRT, SEM, GLM) as well as to approaches from other research fields have been established. In this paper, these…

Methodology · Statistics 2026-05-18 Kevin Kistermann , Vivato V. Andriamiarana , Augustin Kelava

Rejoinder to "Is Bayes Posterior just Quick and Dirty Confidence?" by D. A. S. Fraser [arXiv:1112.5582]

Methodology · Statistics 2012-01-04 D. A. S. Fraser

We consider estimation procedures which are recursive in the sense that each successive estimator is obtained from the previous one by a simple adjustment. We propose a wide class of recursive estimation procedures for the general…

Statistics Theory · Mathematics 2007-05-23 Teo Sharia

Network tomography refers to the use of inference techniques for inferring internal network states from end-to-end probes. Quantum probes, implemented by sending blocks of $n$ coherent-state pulses augmented with continuous-variable (CV)…

Quantum Physics · Physics 2026-04-29 Yufei Zheng , Zihao Gong , Saikat Guha , Don Towsley