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Markov Population Model is a commonly used framework to describe stochastic systems. Their exact analysis is unfeasible in most cases because of the state space explosion. Approximations are usually sought, often with the goal of reducing…

Systems and Control · Computer Science 2014-05-19 Luca Bortolussi , Rytis Paškauskas

We compared the properties of the error threshold transition in quasispecies evolution for three different topologies of the genome space. They are a) hypercube b) rugged landscape modelled by an ultrametric space, and c) holey landscape…

Statistical Mechanics · Physics 2009-11-07 Michal Kolar , Frantisek Slanina

Let the random variable $Z_{n,k}$ denote the number of increasing subsequences of length $k$ in a random permutation from $S_n$, the symmetric group of permutations of $\{1,...,n\}$. In a recent paper [Random Structures Algorithms 29 (2006)…

Probability · Mathematics 2009-09-29 Ross G. Pinsky

The recent work by Dong & Yang (2023) showed for misspecified sparse linear bandits, one can obtain an $O\left(\epsilon\right)$-optimal policy using a polynomial number of samples when the sparsity is a constant, where $\epsilon$ is the…

Machine Learning · Computer Science 2024-07-19 Ally Yalei Du , Lin F. Yang , Ruosong Wang

In statistical inference, confidence set procedures are typically evaluated based on their validity and width properties. Even when procedures achieve rate-optimal widths, confidence sets can still be excessively wide in practice due to…

Statistics Theory · Mathematics 2025-03-20 Kenta Takatsu

This paper focuses on a semiparametric regression model in which the response variable is explained by the sum of two components. One of them is parametric (linear), the corresponding explanatory variable is measured with additive error and…

Methodology · Statistics 2024-11-20 Silvia Novo , Germán Aneiros , Philippe Vieu

In this paper we introduce a mixture cure model with a linear hazard rate regression model for the event times. Cure models are statistical models for event times that take into account that a fraction of the population might never…

Statistics Theory · Mathematics 2020-11-26 Emil Aas Stoltenberg

We study the corrections to $\epsilon^\prime /\epsilon$ in the minimal supersymmetric model at the leading order in QCD and QED. Supersymmetry can increase the standard model prediction for $\epsilon^\prime /\epsilon$ by at most 40\% for…

High Energy Physics - Lattice · Physics 2010-11-01 E. Gabrielli , G. F. Giudice

A key tool in recent advances in understanding arithmetic progressions and other patterns in subsets of the integers is certain norms or seminorms. One example is the norms on $\Z/N\Z$ introduced by Gowers in his proof of Szemer\'edi's…

Dynamical Systems · Mathematics 2007-11-26 Bryna Kra , Bernard Host

We consider how transfer of genetic information between individuals influences the phase diagram and mean fitness of both the Eigen and the parallel, or Crow-Kimura, models of evolution. In the absence of genetic transfer, these physical…

Populations and Evolution · Quantitative Biology 2009-11-13 Jeong-Man Park , Michael W. Deem

Quark-hadron duality in the inclusive semileptonic decay $B\to X_c l\nu$ in the Shifman-Voloshin limit $\Lambda \ll \delta m=m_b - m_c \ll m_b, m_c$ is studied within a nonrelativistic potential model. The integrated semileptonic decay rate…

High Energy Physics - Phenomenology · Physics 2009-10-31 A. Le Yaouanc , D. Melikhov , V. Morenas , L. Oliver , O. Pene , J. -C. Raynal

We prove the existence and uniqueness of a quasi-stationary distribution for three stochastic processes derived from the model of Muller's ratchet. This model was invented with the aim of evaluating the limitations of an asexual…

Probability · Mathematics 2024-04-02 Mauro Mariani , Etienne Pardoux , Aurélien Velleret

The solutions of elliptic problems with a Dirac measure in right-hand side are not H1 and therefore the convergence of the finite element solutions is suboptimal. Graded meshes are standard remedy to recover quasi-optimality, namely…

Numerical Analysis · Mathematics 2015-07-17 Silvia Bertoluzza , Astrid Decoene , Loïc Lacouture , Sébastien Martin

The $k$-mismatch problem consists in computing the Hamming distance between a pattern $P$ of length $m$ and every length-$m$ substring of a text $T$ of length $n$, if this distance is no more than $k$. In many real-world applications, any…

Regularization methods have been recently developed to construct stable approximate solutions to classical partial differential equations considered as final value problems. In this paper, we investigate the backward parabolic problem with…

Analysis of PDEs · Mathematics 2015-10-19 Vo Anh Khoa

Foundation models in genomics have shown mixed success compared to their counterparts in natural language processing. Yet, the reasons for their limited effectiveness remain poorly understood. In this work, we investigate the role of…

Machine Learning · Computer Science 2026-04-07 Maxime Rochkoulets , Lovro Vrček , Mile Šikić

In Bayesian inference, computing the posterior distribution from the data is typically a non-trivial problem, which usually requires approximations such as mean-field approaches or numerical methods, like the Monte Carlo Markov Chain. Being…

Disordered Systems and Neural Networks · Physics 2025-07-29 Alfredo Braunstein , Louise Budzynski , Matteo Mariani , Federico Ricci-Tersenghi

In this paper we study the semiclassical limit for the pseudo-relativistic Hartree equation $\sqrt{-\varepsilon^2 \Delta + m^2}u + V u = (I_\alpha * |u|^{p}) |u|^{p-2}u$ in $\mathbb{R}^N$ where $m>0$, $2 \leq p < \frac{2N}{N-1}$, $V \colon…

Analysis of PDEs · Mathematics 2015-01-27 Silvia Cingolani , Simone Secchi

In a recent letter [Phys. Rev. Lett. {\bf 100}, 164101 (2008)] and within the context of quantized chaotic billiards, random plane wave and semiclassical theoretical approaches were applied to an example of a relatively new class of…

Mesoscale and Nanoscale Physics · Physics 2013-05-29 Denis Ullmo , Steven Tomsovic , Arnd Baecker

Classical statistical learning theory predicts a U-shaped relationship between test loss and model capacity, driven by the bias-variance trade-off. Recent advances in modern machine learning have revealed a more complex pattern,…

Machine Learning · Statistics 2026-04-23 Yin Liu , Jianwen Cai , Didong Li