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Approximate Bayesian computation (ABC) has gained popularity in recent years owing to its easy implementation, nice interpretation and good performance. Its advantages are more visible when one encounters complex models where maximum…

Computation · Statistics 2016-08-19 Xiaolong Zhong , Malay Ghosh

Exponential random graph models are an important tool in the statistical analysis of data. However, Bayesian parameter estimation for these models is extremely challenging, since evaluation of the posterior distribution typically involves…

Computation · Statistics 2017-05-05 Lampros Bouranis , Nial Friel , Florian Maire

It is widely recognised that semiparametric efficient estimation can be hard to achieve in practice: estimators that are in theory efficient may require unattainable levels of accuracy for the estimation of complex nuisance functions. As a…

Statistics Theory · Mathematics 2024-12-18 Elliot H. Young , Rajen D. Shah

Calude, Jain, Khoussainov, Li, and Stephan (2017) proposed a quasi-polynomial-time algorithm solving parity games. After this breakthrough result, a few other quasi-polynomial-time algorithms were introduced; none of them is easy to…

Formal Languages and Automata Theory · Computer Science 2019-04-30 Paweł Parys

We deal with the equivariant estimation of scatter and location for p-dimensional data, giving emphasis to scatter. It it important that the estimators possess both a high efficiency for normal data and a high resistance to outliers, that…

Statistics Theory · Mathematics 2015-08-17 Ricardo A. Maronna , Victor J. Yohai

We want to select the best systems out of a given set of systems (or rank them) with respect to their expected performance. The systems allow random observations only and we assume that the joint observation of the systems has a…

Methodology · Statistics 2017-01-23 Björn Görder , Michael Kolonko

In this paper, we introduce a new semi-discrete modulus of smoothness, which generalizes the definition given by Kolomoitsev and Lomako (KL) in 2023 (in the paper published in the J. Approx. Theory), and we establish very general one- and…

Numerical Analysis · Mathematics 2026-05-28 Danilo Costarelli , Donato Lavella

We improve the classical results by Brenner and Thom\'ee on rational approximations of operator semigroups. In the setting of Hilbert spaces, we introduce a finer regularity scale for initial data, provide sharper stability estimates, and…

Functional Analysis · Mathematics 2024-04-10 Alexander Gomilko , Yuri Tomilov

This paper revisits the performance of Rademacher random projections, establishing novel statistical guarantees that are numerically sharp and non-oblivious with respect to the input data. More specifically, the central result is the…

Machine Learning · Computer Science 2023-03-22 Maciej Skorski , Alessandro Temperoni

Several bivariate beta distributions have been proposed in the literature. In particular, Olkin and Liu (2003) proposed a 3 parameter bivariate beta model, which Arnold and Ng (2011) extend to 5 and 8 parameter models. The 3 parameter model…

Computation · Statistics 2015-08-21 Roberto C. Crackel , James M. Flegal

In this paper we prove local well-posedness for Quasi-linear Scrh\"odinger equations with initial data in unweighted Sobolev Spaces. For small initial data with minimal smoothness this has addressed by J. Marzuola, J. Metcalfe and D.…

Analysis of PDEs · Mathematics 2014-10-02 Nicholas P. Michalowski

The paper presents an elaborated and simplified version of the structural result for branching bisimilarity on normed BPA (Basic Process Algebra) processes that was the crux of a conference paper by Czerwinski and Jancar (arxiv 7/2014 and…

Logic in Computer Science · Computer Science 2019-03-14 Petr Jancar

Recently a number of randomized 3/4-approximation algorithms for MAX SAT have been proposed that all work in the same way: given a fixed ordering of the variables, the algorithm makes a random assignment to each variable in sequence, in…

Data Structures and Algorithms · Computer Science 2013-08-16 Matthias Poloczek , David P. Williamson , Anke van Zuylen

The quantitative analysis of stochastic homogenization problems has been a very active field in the last fifteen years. Whereas the first results were motivated by applied questions (namely, the numerical approximation of homogenized…

Analysis of PDEs · Mathematics 2024-03-01 Antoine Gloria , Siguang Qi

Commonly used in computer vision and other applications, robust PCA represents an algorithmic attempt to reduce the sensitivity of classical PCA to outliers. The basic idea is to learn a decomposition of some data matrix of interest into…

Computer Vision and Pattern Recognition · Computer Science 2016-10-10 Tae-Hyun Oh , Yasuyuki Matsushita , In So Kweon , David Wipf

In analogy with the regularity lemma of Szemer\'edi, regularity lemmas for polynomials shown by Green and Tao (Contrib. Discrete Math. 2009) and by Kaufman and Lovett (FOCS 2008) modify a given collection of polynomials \calF =…

Computational Complexity · Computer Science 2013-11-21 Arnab Bhattacharyya , Pooya Hatami , Madhur Tulsiani

We define the notion of {\em rational presentation of a complete metric space} in order to study metric spaces from the algorithmic complexity point of view. In this setting, we study some presentations of the space $\czu$ of uniformly…

Numerical Analysis · Mathematics 2025-08-22 Henri Lombardi , Salah Labhalla , E. Moutai

The notion of Schnorr randomness refers to computable reals or computable functions. We propose a version of Schnorr randomness for subcomputable classes and characterize it in different ways: by Martin L\"of tests, martingales or measure…

Logic in Computer Science · Computer Science 2019-03-14 Claude Sureson

We prove algorithmic weak and \Szemeredi{} regularity lemmas for several classes of sparse graphs in the literature, for which only weak regularity lemmas were previously known. These include core-dense graphs, low threshold rank graphs,…

Data Structures and Algorithms · Computer Science 2025-05-30 Greg Bodwin , Santosh Vempala

Sequential posted pricing auctions are popular because of their simplicity in practice and their tractability in theory. A usual assumption in their study is that the Bayesian prior distributions of the buyers are known to the seller, while…

Machine Learning · Computer Science 2024-06-14 Sahil Singla , Yifan Wang