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Margin-based structured prediction commonly uses a maximum loss over all possible structured outputs \cite{Altun03,Collins04b,Taskar03}. In natural language processing, recent work \cite{Zhang14,Zhang15} has proposed the use of the maximum…

Machine Learning · Statistics 2018-11-16 Jean Honorio , Tommi Jaakkola

This paper reviews the current state-of-the-art in the simulation of the mechanical behavior of polycrystalline materials by means of computational homogenization. The key ingredients of this modelling strategy are presented in detail…

Materials Science · Physics 2018-11-22 J. Segurado , R. A. Lebensohn , J. LLorca

Increased automation has created an impetus to integrate infrastructure with wide-spread connectivity in order to improve efficiency, sustainability, autonomy, and security. Nonetheless, this reliance on connectivity and the inevitability…

Systems and Control · Electrical Eng. & Systems 2023-11-17 Tanushree Roy , Satadru Dey

Gaussian processes are used in many machine learning applications that rely on uncertainty quantification. Recently, computational tools for working with these models in geometric settings, such as when inputs lie on a Riemannian manifold,…

Machine Learning · Statistics 2023-10-31 Paul Rosa , Viacheslav Borovitskiy , Alexander Terenin , Judith Rousseau

Let A be a matrix, c be any linear objective function and x be a fractional vector, say an LP solution to some discrete optimization problem. Then a recurring task in theoretical computer science (and in approximation algorithms in…

Data Structures and Algorithms · Computer Science 2011-04-26 Thomas Rothvoss

This paper studies the principal component (PC) method-based estimation of weak factor models with sparse loadings. We uncover an intrinsic near-sparsity preservation property for the PC estimators of loadings, which comes from the…

Econometrics · Economics 2024-11-08 Jie Wei , Yonghui Zhang

The large-deviation method allows to characterize an ergodic counting process in terms of a thermodynamic frame where a free energy function determines the asymptotic non-stationary statistical properties of its fluctuations. Here, we study…

Statistical Mechanics · Physics 2011-12-13 Adrian A. Budini

The error exponent in lossy source coding characterizes the asymptotic decay rate of error probability with respect to blocklength. The Marton's error exponent provides the theoretically optimal bound on this rate. However, computation…

Information Theory · Computer Science 2025-07-29 Jiachuan Ye , Shitong Wu , Lingyi Chen , Wenyi Zhang , Huihui Wu , Hao Wu

We derive a functional for the entropy contributed by any microscopic degrees of freedom as arising from their measurable pair correlations. Applicable both in and out of equilibrium, this functional yields the maximum entropy which a…

Statistical Mechanics · Physics 2023-02-17 Benjamin Sorkin , Joshua Ricouvier , Haim Diamant , Gil Ariel

Multi-particle dynamics in one-dimensional asymmetric exclusion processes with disorder is investigated theoretically by computational and analytical methods. It is argued that the general phase diagram consists of three non-equilibrium…

Statistical Mechanics · Physics 2009-11-13 M. Ebrahim Foulaadvand , Anatoly Kolomeisky , Hamid Teymouri

Advancement of chip technology will make future computer chips faster. Power consumption of such chips shall also decrease. But this speed gain shall not come free of cost, there is going to be a trade-off between speed and efficiency, i.e…

Programming Languages · Computer Science 2024-04-29 Dibyendu Das , Soumyajit Dey

A research frontier has emerged in scientific computation, wherein numerical error is regarded as a source of epistemic uncertainty that can be modelled. This raises several statistical challenges, including the design of statistical…

Machine Learning · Statistics 2017-10-19 François-Xavier Briol , Chris. J. Oates , Mark Girolami , Michael A. Osborne , Dino Sejdinovic

In this paper we show that many sequential randomized incremental algorithms are in fact parallel. We consider algorithms for several problems including Delaunay triangulation, linear programming, closest pair, smallest enclosing disk,…

Data Structures and Algorithms · Computer Science 2018-10-15 Guy E. Blelloch , Yan Gu , Julian Shun , Yihan Sun

Bayesian inference involves the specification of a statistical model by a statistician or practitioner, with careful thought about what each parameter represents. This results in particularly interpretable models which can be used to…

Computation · Statistics 2019-08-07 Jonathan Law , Darren Wilkinson

The equivalent permeability of a randomly cracked porous material is studied using a finite element program in which a four-nodes zero-thickness element is implemented for modelling the cracks. The numerical simulations are performed for…

Classical Physics · Physics 2008-10-07 Siavash Ghabezloo , Ahmad Pouya

One approach to confronting computational hardness is to try to understand the contribution of various parameters to the running time of algorithms and the complexity of computational tasks. Almost no computational tasks in real life are…

Computational Complexity · Computer Science 2011-11-23 Rodney G. Downey , Dimitrios M. Thilikos

In this work we consider the problem of extracting a set of interaction parameters from an high-dimensional dataset describing T independent configurations of a complex system composed of N binary units. This problem is formulated in the…

Statistical Mechanics · Physics 2013-11-04 Iacopo Mastromatteo

We introduce $Recursive~Jigsaw~Reconstruction$, a technique for analyzing reconstructed particle interactions in the presence of kinematic and combinatoric unknowns associated with unmeasured and indistinguishable particles, respectively.…

High Energy Physics - Phenomenology · Physics 2017-12-27 Paul Jackson , Christopher Rogan

We consider the problem of computing the convolution of two long vectors using parallel processing units in the presence of "stragglers". Stragglers refer to the small fraction of faulty or slow processors that delays the entire computation…

Information Theory · Computer Science 2017-05-11 Sanghamitra Dutta , Viveck Cadambe , Pulkit Grover

Conditional differential entropy provides an intuitive measure for relatively ranking time-series complexity by quantifying uncertainty in future observations given past context. However, its direct computation for high-dimensional…

Signal Processing · Electrical Eng. & Systems 2025-10-24 Jacob Ayers , Richard Hahnloser , Julia Ulrich , Lothar Sebastian Krapp , Remo Nitschke , Sabine Stoll , Balthasar Bickel , Reinhard Furrer