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Finding analytically the statistics of the longest common subsequence (LCS) of a pair of random sequences drawn from c alphabets is a challenging problem in computational evolutionary biology. We present exact asymptotic results for the…

Genomics · Quantitative Biology 2009-11-10 Satya N. Majumdar , Sergei Nechaev

In this paper, our interest is in the problem of simultaneous hypothesis testing when the test statistics corresponding to the individual hypotheses are possibly correlated. Specifically, we consider the case when the test statistics…

Statistics Theory · Mathematics 2019-01-14 Anupam Kundu , Subir Kumar Bhandari

We study the following rearrangement problem: Given $n$ words, rearrange and concatenate them so that the obtained string is lexicographically smallest (or largest, respectively). We show that this problem reduces to sorting the given words…

Data Structures and Algorithms · Computer Science 2022-04-26 Ruixi Luo , Taikun Zhu , Kai Jin

We discuss a notion of convergence for binary trees that is based on subtree sizes. In analogy to recent developments in the theory of graphs, posets and permutations we investigate some general aspects of the topology, such as a…

Combinatorics · Mathematics 2024-02-14 Rudolf Grübel

We consider training and testing on mixture distributions with different training and test proportions. We show that in many settings, and in some sense generically, distribution shift can be beneficial, and test performance can improve due…

Machine Learning · Computer Science 2025-11-11 Marko Medvedev , Kaifeng Lyu , Zhiyuan Li , Nathan Srebro

This paper introduces a statistical test inferring whether a variable allows separating two classes by means of a single critical value. Its test statistic is the prediction error of a nonparametric threshold classifier. While this approach…

Methodology · Statistics 2017-07-17 Fabian Schroeder

We consider random graphs with a given degree sequence and show, under weak technical conditions, asymptotic normality of the number of components isomorphic to a given tree, first for the random multigraph given by the configuration model…

Probability · Mathematics 2019-02-01 Svante Janson

In this paper we study bipartite quantum correlations using techniques from tracial noncommutative polynomial optimization. We construct a hierarchy of semidefinite programming lower bounds on the minimal entanglement dimension of a…

Optimization and Control · Mathematics 2018-01-10 Sander Gribling , David de Laat , Monique Laurent

Selecting N random points in a unit square corresponds to selecting a random permutation. By putting 5 types of symmetry restrictions on the points, we obtain subsets of permutations : involutions, signed permutations and signed…

Combinatorics · Mathematics 2007-05-23 Jinho Baik , Eric M. Rains

In this paper, we consider robust control using randomized algorithms. We extend the existing order statistics distribution theory to the general case in which the distribution of population is not assumed to be continuous and the order…

Optimization and Control · Mathematics 2008-05-13 Xinjia Chen , Kemin Zhou

This paper develops a framework for the design of scoring rules to optimally incentivize an agent to exert a multi-dimensional effort. This framework is a generalization to strategic agents of the classical knapsack problem (cf. Briest,…

Computer Science and Game Theory · Computer Science 2023-07-03 Jason D. Hartline , Liren Shan , Yingkai Li , Yifan Wu

This paper deals with the following question: Suppose that there exist an integer or a non-negative integer solution $x$ to a system $Ax = b$, where the number of non-zero components of $x$ is $n$. The target is, for a given natural number…

Optimization and Control · Mathematics 2026-02-12 Stefan Kuhlmann , Timm Oertel , Robert Weismantel

We consider the concatenation of $t$ uniformly random perfect matchings on $2n$ vertices, where the operation of concatenation is inspired by the multiplication of generators of the Brauer algebra $\mathfrak{B}_n(\delta)$. For the resulting…

Probability · Mathematics 2024-10-30 Fabian Burghart , Paul Thévenin

In multiple classification, one aims to determine whether a testing sequence is generated from the same distribution as one of the M training sequences or not. Unlike most of existing studies that focus on discrete-valued sequences with…

Machine Learning · Statistics 2024-10-30 Lina Zhu , Lin Zhou

We prove that a suitably de-biased version of Chatterjee's rank correlation based on i.i.d. copies of a random vector $(X,Y)$ is asymptotically normal whenever $Y$ is not almost surely constant. No further conditions on the joint…

Probability · Mathematics 2025-05-19 Marius Kroll

Ranking alternatives is a natural way for humans to explain their preferences. It is being used in many settings, such as school choice, course allocations and residency matches. In some cases, several `items' are given to each participant.…

Computer Science and Game Theory · Computer Science 2022-12-06 Erel Segal-Halevi , Haris Aziz , Avinatan Hassidim

We present theoretical guarantees for an alternating minimization algorithm for the dictionary learning/sparse coding problem. The dictionary learning problem is to factorize vector samples $y^{1},y^{2},\ldots, y^{n}$ into an appropriate…

Machine Learning · Statistics 2019-08-01 Niladri S. Chatterji , Peter L. Bartlett

The discrepancy between two independent samples \(X_1,\dots,X_n\) and \(Y_1,\dots,Y_n\) drawn from the same distribution on $\mathbb{R}^d$ typically has order \(O(\sqrt{n})\) even in one dimension. We give a simple online algorithm that…

Probability · Mathematics 2026-01-23 Gleb Smirnov , Roman Vershynin

There are two methods for counting the number of occurrences of a string in another large string. One is to count the number of places where the string is found. The other is to determine how many pieces of string can be extracted without…

Data Structures and Algorithms · Computer Science 2022-11-09 Ayaka Takamoto , Mitsuo Yoshida , Kyoji Umemura

In this work, we aim to calibrate the score outputs of an estimator for the binary classification problem by finding an 'optimal' mapping to class probabilities, where the 'optimal' mapping is in the sense that minimizes the classification…

Machine Learning · Computer Science 2021-08-20 Kaan Gokcesu , Hakan Gokcesu