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This paper presents a novel approach to estimate the Standard Model backgrounds based on modifying Monte Carlo predictions within their systematic uncertainties. The improved background model is obtained by altering the original predictions…

High Energy Physics - Experiment · Physics 2009-11-23 S. Caron , G. Cowan , E. Gross , S. Horner , J. E. Sundermann

In this letter, we consider the problem of field estimation using binary measurements. Previous work has formulated the problem as a parameter estimation problem, with the parameter estimation carried out in an online manner using…

Methodology · Statistics 2022-09-14 Alex S. Leong , Mohammad Zamani , Iman Shames

We present and empirically evaluate an efficient algorithm that learns to aggregate the predictions of an ensemble of binary classifiers. The algorithm uses the structure of the ensemble predictions on unlabeled data to yield significant…

Machine Learning · Computer Science 2015-11-12 Akshay Balsubramani , Yoav Freund

The trace of a matrix function f(A), most notably of the matrix inverse, can be estimated stochastically using samples< x,f(A)x> if the components of the random vectors x obey an appropriate probability distribution. However such a…

Numerical Analysis · Mathematics 2021-08-26 Andreas Frommer , Mostafa Nasr Khalil , Gustavo Ramirez-Hidalgo

Stability selection represents an attractive approach to identify sparse sets of features jointly associated with an outcome in high-dimensional contexts. We introduce an automated calibration procedure via maximisation of an in-house…

We propose a very fast approximate Markov Chain Monte Carlo (MCMC) sampling framework that is applicable to a large class of sparse Bayesian inference problems, where the computational cost per iteration in several models is of order…

Computation · Statistics 2021-08-17 Yves Atchadé , Liwei Wang

This paper investigates the problem of simultaneously predicting multiple binary responses by utilizing a shared set of covariates. Our approach incorporates machine learning techniques for binary classification, without making assumptions…

Methodology · Statistics 2024-03-07 The Tien Mai

The Ising model was originally developed to model magnetisation of solids in statistical physics. As a network of binary variables with the probability of becoming 'active' depending only on direct neighbours, the Ising model appears…

Statistics Theory · Mathematics 2018-07-31 Lourens Waldorp , Maarten Marsman , Gunter Maris

We present a polynomial-time Markov chain Monte Carlo algorithm for estimating the partition function of the antiferromagnetic Ising model on any line graph. The analysis of the algorithm exploits the "winding" technology devised by…

Data Structures and Algorithms · Computer Science 2021-03-17 Martin Dyer , Marc Heinrich , Mark Jerrum , Haiko Müller

The determination of transverse single-spin asymmetries in experiments involving polarized targets and/or beams may encounter challenges when (1) the magnitude of the polarization varies greatly with time, (2) the polarization magnitude is…

High Energy Physics - Experiment · Physics 2026-02-27 S. F. Pate , H. Arachchige , C. Kuruppu , D. Nawarathne

Atomistic simulations provide valuable insights into the physical processes governing material behavior. However, their applicability is fundamentally constrained by the limited time scales accessible to brute-force simulations. This…

Computational Physics · Physics 2026-02-16 Michael Kim , Wei Cai

We consider the problem of estimating the autocorrelation operator of an autoregressive Hilbertian process. By means of a Tikhonov approach, we establish a general result that yields the convergence rate of the estimated autocorrelation…

Statistics Theory · Mathematics 2022-06-09 Alessia Caponera , Victor M. Panaretos

When dealing with difficult inverse problems such as inverse rendering, using Monte Carlo estimated gradients to optimise parameters can slow down convergence due to variance. Averaging many gradient samples in each iteration reduces this…

Graphics · Computer Science 2023-09-28 Martin Balint , Karol Myszkowski , Hans-Peter Seidel , Gurprit Singh

In this paper, we consider the Markov-Chain Monte Carlo (MCMC) approach for random sampling of combinatorial objects. The running time of such an algorithm depends on the total mixing time of the underlying Markov chain and is unknown in…

Discrete Mathematics · Computer Science 2016-09-15 Steffen Rechner , Annabell Berger

The two point angular correlation function is an excellent measure of structure in the universe. To extract from it the three dimensional power spectrum, one must invert Limber's Equation. Here we perform this inversion using a Bayesian…

Astrophysics · Physics 2008-11-26 Scott Dodelson , Enrique Gaztanaga

Record linkage is the process of matching together records from different data sources that belong to the same entity. Record linkage is increasingly being used by many organizations including statistical, health, government etc. to link…

Computation · Statistics 2020-11-26 Shovanur Haque , Kerrie Mengersen

Since Hamming distances can be calculated by bitwise computations, they can be calculated with less computational load than L2 distances. Similarity searches can therefore be performed faster in Hamming distance space. The elements of…

Machine Learning · Computer Science 2013-03-19 Yui Noma , Makiko Konoshima

The physical design process of large-scale designs is a time-consuming task, often requiring hours to days to complete, with routing being the most critical and complex step. As the the complexity of Integrated Circuits (ICs) increases,…

Machine Learning · Computer Science 2023-08-02 Biao Liu , Congyu Qiao , Ning Xu , Xin Geng , Ziran Zhu , Jun Yang

This paper describes a method for the recovering of software architectures from a set of similar (but unrelated) software products in binary form. One intention is to drive refactoring into software product lines and combine architecture…

Software Engineering · Computer Science 2016-08-08 Ian D. Peake , Jan Olaf Blech , Lasith Fernando , Divyasheel Sharma , Srini Ramaswamy , Mallikarjun Kande

The clustering of autonomous driving scenario data can substantially benefit the autonomous driving validation and simulation systems by improving the simulation tests' completeness and fidelity. This article proposes a comprehensive data…

Computer Vision and Pattern Recognition · Computer Science 2021-03-31 Jinxin Zhao , Jin Fang , Zhixian Ye , Liangjun Zhang