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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

We study the space requirements of a sorting algorithm where only items that at the end will be adjacent are kept together. This is equivalent to the following combinatorial problem: Consider a string of fixed length n that starts as a…

Probability · Mathematics 2007-05-23 Svante Janson

In this research the technology of complex Markov chains is applied to predict financial time series. The main distinction of complex or high-order Markov Chains and simple first-order ones is the existing of aftereffect or memory. The…

Statistical Finance · Quantitative Finance 2011-11-23 Vladimir Soloviev , Vladimir Saptsin , Dmitry Chabanenko

We consider the problem of sorting $n$ elements in the case of \emph{persistent} comparison errors. In this model (Braverman and Mossel, SODA'08), each comparison between two elements can be wrong with some fixed (small) probability $p$,…

Data Structures and Algorithms · Computer Science 2018-04-23 Barbara Geissmann , Stefano Leucci , Chih-Hung Liu , Paolo Penna

We introduce a novel framework for analyzing sorting algorithms in pairwise ranking prompting (PRP), re-centering the cost model around LLM inferences rather than traditional pairwise comparisons. While classical metrics based on comparison…

Computation and Language · Computer Science 2025-06-02 Juan Wisznia , Cecilia Bolaños , Juan Tollo , Giovanni Marraffini , Agustín Gianolini , Noe Hsueh , Luciano Del Corro

We continue the study of selection and sorting of $n$ numbers under the adversarial comparator model, where comparisons can be adversarially tampered with if the arguments are sufficiently close. We derive a randomized sorting algorithm…

Data Structures and Algorithms · Computer Science 2025-09-09 Chris Trevisan

There has been surprisingly little work on algorithms for sorting strings on distributed-memory parallel machines. We develop efficient algorithms for this problem based on the multi-way merging principle. These algorithms inspect only…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-24 Timo Bingmann , Peter Sanders , Matthias Schimek

To better understand the flows of ideas or information through social and biological systems, researchers develop maps that reveal important patterns in network flows. In practice, network flow models have implied memoryless first-order…

Social and Information Networks · Computer Science 2016-06-28 Christian Persson , Ludvig Bohlin , Daniel Edler , Martin Rosvall

A fundamental algorithm for selecting ranks from a finite subset of an ordered set is Radix Selection. This algorithm requires the data to be given as strings of symbols over an ordered alphabet, e.g., binary expansions of real numbers. Its…

Probability · Mathematics 2017-10-04 Kevin Leckey , Ralph Neininger , Henning Sulzbach

The objective behind the Twin Sort technique is to sort the list of unordered data elements efficiently and to allow efficient and simple arrangement of data elements within the data structure with optimization of comparisons and iterations…

Data Structures and Algorithms · Computer Science 2017-10-24 Veeresh D , Thimmaraju S. N , Ravish G. K

Rank aggregation systems collect ordinal preferences from individuals to produce a global ranking that represents the social preference. Rank-breaking is a common practice to reduce the computational complexity of learning the global…

Machine Learning · Computer Science 2016-10-10 Ashish Khetan , Sewoong Oh

Many latent (factorized) models have been proposed for recommendation tasks like collaborative filtering and for ranking tasks like document or image retrieval and annotation. Common to all those methods is that during inference the items…

Machine Learning · Computer Science 2012-10-19 Jason Weston , John Blitzer

A common way of doing algorithm selection is to train a machine learning model and predict the best algorithm from a portfolio to solve a particular problem. While this method has been highly successful, choosing only a single algorithm has…

Artificial Intelligence · Computer Science 2013-11-19 Lars Kotthoff

We present a deterministic comparison-based algorithm that sorts sequences avoiding a fixed permutation $\pi$ in linear time, even if $\pi$ is a priori unkown. Moreover, the dependence of the multiplicative constant on the pattern $\pi$…

Data Structures and Algorithms · Computer Science 2024-09-13 Michal Opler

We introduce a sorting machine consisting of $k+1$ stacks in series: the first $k$ stacks can only contain elements in decreasing order from top to bottom, while the last one has the opposite restriction. This device generalizes \cite{SM},…

Data Structures and Algorithms · Computer Science 2019-10-10 Giulio Cerbai , Lapo Cioni , Luca Ferrari

A decision maker records measurements of a finite-state Markov chain corrupted by noise. The goal is to decide when the Markov chain hits a specific target state. The decision maker can choose from a finite set of sampling intervals to pick…

Optimization and Control · Mathematics 2012-08-17 Vikram Krishnamurthy

Semi-Markov processes are Markovian processes in which the firing time of the transitions is modelled by probabilistic distributions over positive reals interpreted as the probability of firing a transition at a certain moment in time. In…

Formal Languages and Automata Theory · Computer Science 2017-12-04 Mathias Ruggaard Pedersen , Nathanaël Fijalkow , Giorgio Bacci , Kim Guldstrand Larsen , Radu Mardare

We study sorting algorithms based on randomized round-robin comparisons. Specifically, we study Spin-the-bottle sort, where comparisons are unrestricted, and Annealing sort, where comparisons are restricted to a distance bounded by a…

Data Structures and Algorithms · Computer Science 2015-03-17 Michael T. Goodrich

In scientific computing, it is common that a mathematical expression can be computed by many different algorithms (sometimes over hundreds), each identifying a specific sequence of library calls. Although mathematically equivalent, those…

Performance · Computer Science 2021-09-15 Aravind Sankaran , Paolo Bientinesi

Sampling from combinatorial families can be difficult. However, complicated families can often be embedded within larger, simpler ones, for which easy sampling algorithms are known. We take advantage of such a relationship to describe a…

Data Structures and Algorithms · Computer Science 2013-09-02 James Y. Zhao
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