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Chernoff approximations to strongly continuous one-parameter semigroups give solutions to a wide class of differential equations. This paper studies the rate of convergence of the Chernoff approximations. We provide simple natural examples…

Functional Analysis · Mathematics 2021-11-02 Oleg E. Galkin , Ivan D. Remizov

Qualitative probabilistic networks have been designed for probabilistic reasoning in a qualitative way. Due to their coarse level of representation detail, qualitative probabilistic networks do not provide for resolving trade-offs and…

Artificial Intelligence · Computer Science 2013-01-18 Silja Renooij , Linda C. van der Gaag , Simon Parsons , Shaw Green

This paper introduces a generic method which enables to use conventional deep neural networks as end-to-end one-class classifiers. The method is based on splitting given data from one class into two subsets. In one-class classification,…

Machine Learning · Computer Science 2019-09-17 Patrick Schlachter , Yiwen Liao , Bin Yang

This paper is on developing some computer-assisted proof methods involving non-classical inequalities for Shannon entropy. Two areas of the applications of information inequalities are studied: Secret sharing schemes and hat guessing games.…

Information Theory · Computer Science 2023-10-19 Emirhan Gürpınar

Balls-and-bins games have been a wildly successful tool for modeling load balancing problems. In this paper, we study a new scenario, which we call the ball recycling game, defined as follows: Throw m balls into n bins i.i.d. according to a…

Data Structures and Algorithms · Computer Science 2018-11-05 Michael A. Bender , Jake Christensen , Alex Conway , Martín Farach-Colton , Rob Johnson , Meng-Tsung Tsai

This paper studies the trade-off between two different kinds of pure exploration: breadth versus depth. The most biased coin problem asks how many total coin flips are required to identify a "heavy" coin from an infinite bag containing both…

Machine Learning · Computer Science 2016-03-29 Kevin Jamieson , Daniel Haas , Ben Recht

The forward-backward splitting technique is a popular method for solving monotone inclusions that has applications in optimization. In this paper we explore the behaviour of the algorithm when the inclusion problem has no solution. We…

Optimization and Control · Mathematics 2016-08-09 Walaa M. Moursi

Data deduplication emerged as a powerful solution for reducing storage and bandwidth costs in cloud settings by eliminating redundancies at the level of chunks. This has spurred the development of numerous Content-Defined Chunking (CDC)…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-22 Marcel Gregoriadis , Leonhard Balduf , Björn Scheuermann , Johan Pouwelse

We study the following synchronous process that we call "repeated balls-into-bins". The process is started by assigning $n$ balls to $n$ bins in an arbitrary way. In every subsequent round, from each non-empty bin one ball is chosen…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-25 Luca Becchetti , Andrea Clementi , Emanuele Natale , Francesco Pasquale , Gustavo Posta

The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on…

Physics and Society · Physics 2012-03-29 Andrea Lancichinetti , Santo Fortunato

In this paper we address some questions about symmetry, radial monotonicity, and uniqueness for a semilinear fourth-order boundary value problem in the ball of $\mathbb R^2$ deriving from the Kirchhoff-Love model of deformations of thin…

Analysis of PDEs · Mathematics 2025-03-19 Giulio Romani

Allocation of balls into bins is a well studied abstraction for load balancing problems.The literature hosts numerous results for sequential(single dimensional) allocation case when m balls are thrown into n bins. In this paper we study the…

Data Structures and Algorithms · Computer Science 2011-11-30 Ankur Narang , Sourav Dutta , Souvik Bhattacherjee

Clustering is a fundamental problem in data analysis. In differentially private clustering, the goal is to identify $k$ cluster centers without disclosing information on individual data points. Despite significant research progress, the…

Machine Learning · Computer Science 2021-12-30 Edith Cohen , Haim Kaplan , Yishay Mansour , Uri Stemmer , Eliad Tsfadia

In the classical balls-and-bins model, $m$ balls are allocated into $n$ bins one by one uniformly at random. In this note, we consider the $d$-thinning variant of this model, in which the process is regulated in an on-line fashion as…

Probability · Mathematics 2020-01-06 Ohad N. Feldheim , Jiange Li

In a fixed-confidence pure exploration problem in stochastic multi-armed bandits, an algorithm iteratively samples arms and should stop as early as possible and return the correct answer to a query about the arms distributions. We are…

Machine Learning · Computer Science 2025-02-04 Adrienne Tuynman , Rémy Degenne

Contention resolution addresses the problem of coordinating access to a shared communication channel. Time is discretized into synchronized slots, and a packet can be sent in any slot. If no packet is sent, then the slot is empty; if a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-22 Umesh Biswas , Trisha Chakraborty , Maxwell Young

Designing algorithms for balanced allocation of clients to servers in dynamic settings is a challenging problem for a variety of reasons. Both servers and clients may be added and/or removed from the system periodically, and the main…

Data Structures and Algorithms · Computer Science 2017-07-28 Vahab Mirrokni , Mikkel Thorup , Morteza Zadimoghaddam

We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random walk on a regular Markov chain and a Hermitian matrix-valued…

Machine Learning · Statistics 2020-10-30 Jiezhong Qiu , Chi Wang , Ben Liao , Richard Peng , Jie Tang

Many combinatorial optimization problems such as the bin packing and multiple knapsack problems involve assigning a set of discrete objects to multiple containers. These problems can be used to model task and resource allocation problems in…

Artificial Intelligence · Computer Science 2011-10-12 A. S. Fukunaga , R. E. Korf

Dichotomy theorems, which characterize the conditions under which a problem can be solved efficiently, have helped identify important tractability borders for as probabilistic query evaluation, view maintenance, query containment (among…

Databases · Computer Science 2024-05-09 Neha Makhija