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Approximate Bayesian computation (ABC) is a widely used inference method in Bayesian statistics to bypass the point-wise computation of the likelihood. In this paper we develop theoretical bounds for the distance between the statistics used…

Statistics Theory · Mathematics 2019-01-03 James Ridgway

Security Assurance Cases (SAC) are a form of structured argumentation used to reason about the security properties of a system. After the successful adoption of assurance cases for safety, SACs are getting significant traction in recent…

Software Engineering · Computer Science 2020-04-01 Mazen Mohamad , Jan-Philipp Steghöfer , Riccardo Scandariato

We consider the problem of shared randomness-assisted multiple access channel (MAC) simulation for product inputs and characterize the one-shot communication cost region via almost-matching inner and outer bounds in terms of the smooth…

Information Theory · Computer Science 2026-03-26 Aditya Nema , Sreejith Sreekumar , Mario Berta

Clustering algorithms are fundamental tools across many fields, with density-based methods offering particular advantages in identifying arbitrarily shaped clusters and handling noise. However, their effectiveness is often limited by the…

Machine Learning · Computer Science 2025-12-01 Meysam Shirdel Bilehsavar , Razieh Ghaedi , Samira Seyed Taheri , Xinqi Fan , Christian O'Reilly

Cryptographic hash functions for calculating the message digest of a message has been in practical use as an effective measure to maintain message integrity since a few decades. This message digest is unique, irreversible and avoids all…

Cryptography and Security · Computer Science 2010-03-31 Rakesh Mohanty , Niharjyoti Sarangi , Sukant kumar Bishi

The Swift AGN and Cluster Survey (SACS) uses 125 deg^2 of Swift XRT serendipitous fields with variable depths surrounding gamma-ray bursts to provide a medium depth (4e-15 erg/s/cm^2) and area survey filling the gap between deep, narrow…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-27 Xinyu Dai , Rhiannon D. Griffin , Christopher S. Kochanek , Jenna M. Nugent , Joel N. Bregman

We investigate the possible accuracy that can be reached by analytical models for the matter density power spectrum and correlation function. Using a realistic description of the power spectrum that combines perturbation theory with a halo…

Cosmology and Nongalactic Astrophysics · Physics 2014-01-17 Patrick Valageas

We study the maximum information gain that an adversary may obtain through hacking without being detected. Consider a dynamical process observed by a sensor that transmits a local estimate of the system state to a remote estimator according…

Systems and Control · Electrical Eng. & Systems 2020-11-10 Jingyi Lu , Daniel Quevedo , Vijay Gupta , Subhrakanti Dey

We present an experimental study of the influence of quenched disorder on the distribution of flux avalanches in type-II superconductors. In the presence of much quenched disorder, the avalanche sizes are power-law distributed and show…

Statistical Mechanics · Physics 2009-11-10 M. S. Welling , C. M. Aegerter , R. J. Wijngaarden

We present a new variable-length computation-friendly encoding scheme, named SFDC (Succinct Format with Direct aCcesibility), that supports direct and fast accessibility to any element of the compressed sequence and achieves compression…

Data Structures and Algorithms · Computer Science 2023-04-03 Domenico Cantone , Simone Faro

Denial Constraint (DC) is a well-established formalism that captures a wide range of integrity constraints commonly encountered, including candidate keys, functional dependencies, and ordering constraints, among others. Given their…

Databases · Computer Science 2023-09-25 Zifan Liu , Shaleen Deep , Anna Fariha , Fotis Psallidas , Ashish Tiwari , Avrilia Floratou

We develop an analytic model for the hierarchical correlation amplitudes S_j(R)= \bxi_j(R)/\bxi_2^{j-1}(R) of density peaks and dark matter halos in the quasi-linear regime. The statistical distribution of density peaks and dark matter…

Astrophysics · Physics 2015-06-24 H. J. Mo , Y. P. Jing , S. D. M. White

We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called {em probabilistic arc consistency}, which is both a generalization of a well known algorithm for arc consistency used in…

Artificial Intelligence · Computer Science 2013-01-18 Michael C. Horsch , Bill Havens

We present here a status update on the ASCA Hard Serendipitous Survey (HSS), a survey program conducted in the 2-10 keV energy band. In particular we discuss the number-flux relationship, the 2-10 keV spectral properties of the sources and…

Astrophysics · Physics 2007-05-23 R. Della Ceca , V. Braito , I. Cagnoni , T. Maccacaro

Software composition analysis (SCA) denotes the process of identifying open-source software components in an input software application. SCA has been extensively developed and adopted by academia and industry. However, we notice that the…

Software Engineering · Computer Science 2024-12-03 Huaijin Wang , Zhibo Liu , Yanbo Dai , Shuai Wang , Qiyi Tang , Sen Nie , Shi Wu

In real-world applications, observations are often constrained to a small fraction of a system. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and cannot be overcome by longer sampling.…

Data Analysis, Statistics and Probability · Physics 2017-06-02 Anna Levina , Viola Priesemann

While classical chaos is defined via a system's sensitive dependence on its initial conditions (SDIC), this notion does not directly extend to quantum systems. Instead, recent works have established defining both quantum and classical chaos…

Chaotic Dynamics · Physics 2025-12-15 Nachiket Karve , Nathan Rose , David Campbell

Clustering short text embeddings is a foundational task in natural language processing, yet remains challenging due to the need to specify the number of clusters in advance. We introduce a scalable spectral method that estimates the number…

Machine Learning · Computer Science 2025-11-26 Nikita Neveditsin , Pawan Lingras , Vijay Mago

When data is scarce or mistakes are costly, average-case metrics fall short. What a practitioner needs is a guarantee: with probability at least $1-\delta$, the learned policy is $\varepsilon$-close to optimal after $N$ episodes. This is…

Machine Learning · Computer Science 2026-03-03 Joshua Steier

In high dimensional percolation at parameter $p < p_c$, the one-arm probability $\pi_p(n)$ is known to decay exponentially on scale $(p_c - p)^{-1/2}$. We show the same statement for the ratio $\pi_p(n) / \pi_{p_c}(n)$, establishing a form…

Probability · Mathematics 2021-08-02 Shirshendu Chatterjee , Jack Hanson , Philippe Sosoe