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The uniform distribution on matrices with specified row and column sums is often a natural choice of null model when testing for structure in two-way tables (binary or nonnegative integer). Due to the difficulty of sampling from this…

Computation · Statistics 2013-08-14 Jeffrey W. Miller , Matthew T. Harrison

We introduce a new combinatorial structure: the superselector. We show that superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multi-channel…

Data Structures and Algorithms · Computer Science 2010-10-07 Ferdinando Cicalese , Ugo Vaccaro

We consider a dynamical system with finitely many equilibria and perturbed by small noise, in addition to being controlled by an `expensive' control. The controlled process is optimal for an ergodic criterion with a running cost that…

Probability · Mathematics 2019-03-20 Ari Arapostathis , Anup Biswas , Vivek S. Borkar

We study random points on the real line generated by the eigenvalues in unitary invariant random matrix ensembles or by more general repulsive particle systems. As the number of points tends to infinity, we prove convergence of the…

Probability · Mathematics 2015-11-11 Kristina Schubert , Martin Venker

It is, perhaps, surprising that the location of the unique supremum of a stationary process on an interval can fail to be uniformly distributed over that interval. We show that this distribution is absolutely continuous in the interior of…

Probability · Mathematics 2013-10-04 Gennady Samorodnitsky , Yi Shen

We study the statistical mechanics of a class of problems whose phase space is the set of permutations of an ensemble of quenched random positions. Specific examples analyzed are the finite temperature traveling salesman problem on several…

Disordered Systems and Neural Networks · Physics 2009-11-11 David S. Dean , David Lancaster , Satya. N. Majumdar

We initiate the rigorous study of classification in semimetric spaces, which are point sets with a distance function that is non-negative and symmetric, but need not satisfy the triangle inequality. For metric spaces, the doubling dimension…

Machine Learning · Computer Science 2015-02-24 Lee-Ad Gottlieb , Aryeh Kontorovich

Solving population balance equations, we derive analytical steady-state cell size distributions for single-lineage experiments, such as the mother machine. These experiments are fundamentally different from batch cultures where populations…

Populations and Evolution · Quantitative Biology 2023-09-13 Arthur Genthon

We revisit a version of the classic occupancy scheme, where balls are thrown until almost all boxes receive a given number of balls. Special cases are widely known as coupon-collectors and dixie cup problems. We show that as the number of…

Probability · Mathematics 2025-06-26 Alexander Gnedin , Svante Janson , Yaakov Malinovsky

Locating a target is key in many applications, namely in high-stakes real-world scenarios, like detecting humans or obstacles in vehicular networks. In scenarios where precise statistics of the measurement noise are unavailable,…

Optimization and Control · Mathematics 2022-08-17 João Domingos , Cláudia Soares , João Xavier

The principle of maximum entropy provides a useful method for inferring statistical mechanics models from observations in correlated systems, and is widely used in a variety of fields where accurate data are available. While the assumptions…

Neurons and Cognition · Quantitative Biology 2017-06-02 Ulisse Ferrari , Tomoyuki Obuchi , Thierry Mora

Many real world networks, such as social networks, are primarily formed through local interactions between agents. Additionally, in contrast with common network models, social and biological networks exhibit a high degree of clustering.…

Physics and Society · Physics 2015-03-10 Navid Dianati , Nima Dehmamy

Session-based recommenders, used for making predictions out of users' uninterrupted sequences of actions, are attractive for many applications. Here, for this task we propose using metric learning, where a common embedding space for…

Information Retrieval · Computer Science 2021-01-08 Bartłomiej Twardowski , Paweł Zawistowski , Szymon Zaborowski

In large venues like shopping malls and airports, knowledge on the indoor populations fuels applications such as business analytics, venue management, and safety control. In this work, we provide means of modeling populations in partitions…

Databases · Computer Science 2024-10-30 Xiao Li , Huan Li , Hua Lu , Christian S. Jensen

In rank aggregation, members of a population rank issues to decide which are collectively preferred. We focus instead on identifying divisive issues that express disagreements among the preferences of individuals. We analyse the properties…

Multiagent Systems · Computer Science 2023-06-16 Rachael Colley , Umberto Grandi , César Hidalgo , Mariana Macedo , Carlos Navarrete

We give an algorithm that generates a uniformly random contingency table with specified marginals, i.e. a matrix with non-negative integer values and specified row and column sums. Such algorithms are useful in statistics and combinatorics.…

Combinatorics · Mathematics 2021-06-17 Andrii Arman , Pu Gao , Nicholas Wormald

Specifying a proper input distribution is often a challenging task in simulation modeling. In practice, there may be multiple plausible distributions that can fit the input data reasonably well, especially when the data volume is not large.…

Methodology · Statistics 2019-03-15 Weiwei Fan , L. Jeff Hong , Xiaowei Zhang

In random sequential covering, identical objects are deposited randomly, irreversibly, and sequentially; only attempts increasing the coverage are accepted. A finite system eventually gets congested, and we study the statistics of congested…

Probability · Mathematics 2023-03-28 P. L. Krapivsky

We report on two series of experiments, conducted in the frame of two different collaborations designed to study how pedestrians adapt their trajectories and velocities in groups or crowds. Strong emphasis is put on the motivations for the…

Whereas most dimensionality reduction techniques (e.g. PCA, ICA, NMF) for multivariate data essentially rely on linear algebra to a certain extent, summarizing ranking data, viewed as realizations of a random permutation $\Sigma$ on a set…

Machine Learning · Statistics 2019-09-02 Mastane Achab , Anna Korba , Stephan Clémençon