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We present a technique for clustering categorical data by generating many dissimilarity matrices and averaging over them. We begin by demonstrating our technique on low dimensional categorical data and comparing it to several other…

Machine Learning · Statistics 2017-09-20 Saeid Amiri , Bertrand Clarke , Jennifer Clarke

We apply a common measure of randomness, the entropy, in the context of iterated functions on a finite set with n elements. For a permutation, it turns out that this entropy is asymptotically (for a growing number of iterations) close to…

Number Theory · Mathematics 2017-12-20 Joachim von zur Gathen

Some models of clustering processes are formulated and analytically solved employing generating functions methods. Those models include events which result from combined action of the coagulation and fragmentation processes. Fragmentation…

Statistical Mechanics · Physics 2009-11-07 Vladimir M. Dubovik , Arkadi G. Galperin , Viktor S. Richvitsky , Aleksey A. Lushnikov

We consider the enumeration of pattern-avoiding involutions, focusing in particular on sets defined by avoiding a single pattern of length 4. As we demonstrate, the numerical data for these problems demonstrates some surprising behavior.…

Combinatorics · Mathematics 2014-09-15 Miklós Bóna , Cheyne Homberger , Jay Pantone , Vincent Vatter

Bivariate generating functions for various subsets of the class of permutations containing no descending sequence of length three or more are determined. The notion of absolute indecomposability of a permutation is introduced, and used in…

Combinatorics · Mathematics 2015-08-07 Michael H. Albert

Let $X,X_1,X_2,\ldots$ be i.i.d. mean zero random vectors with values in a separable Banach space $B$, $S_n=X_1+\cdots+X_n$ for $n\ge1$, and assume $\{c_n:n\ge1\}$ is a suitably regular sequence of constants. Furthermore, let…

Probability · Mathematics 2014-03-28 Uwe Einmahl , Jim Kuelbs

For uniform random permutations conditioned to have no long cycles, we prove that the total number of cycles satisfies a central limit theorem. Under additional assumptions on the asymptotic behavior of the set of allowed cycle lengths, we…

Probability · Mathematics 2016-08-31 Volker Betz , Helge Schäfer

We bound the number of permutations with a fixed number $r$ of $321 \ominus p_0$ patterns by a constant times the number of permutations which avoid $321 \ominus p_0$. We use this new upper bound to show that the ordinary generating…

Combinatorics · Mathematics 2025-10-29 Michael Waite

A composition of a nonnegative integer (n) is a sequence of positive integers whose sum is (n). A composition is palindromic if it is unchanged when its terms are read in reverse order. We provide a generating function for the number of…

Combinatorics · Mathematics 2007-05-23 Sergey Kitaev , Tyrrell B. McAllister , T. Kyle Petersen

The study of pattern containment and avoidance for linear permutations is a well-established area of enumerative combinatorics. A cyclic permutation is the set of all rotations of a linear permutation. Callan initiated the study of…

The determination of cluster centers generally depends on the scale that we use to analyze the data to be clustered. Inappropriate scale usually leads to unreasonable cluster centers and thus unreasonable results. In this study, we first…

Machine Learning · Statistics 2016-10-20 Xiurui Geng , Hairong Tang

We initiate a general approach for the fast enumeration of permutations with a prescribed number of occurrences of `forbidden' patterns, that seems to indicate that the enumerating sequence is always P-recursive. We illustrate the method…

Combinatorics · Mathematics 2007-05-23 John Noonan , Doron Zeilberger

We study supervised learning problems using clustering constraints to impose structure on either features or samples, seeking to help both prediction and interpretation. The problem of clustering features arises naturally in text…

Machine Learning · Computer Science 2016-09-20 Vincent Roulet , Fajwel Fogel , Alexandre d'Aspremont , Francis Bach

An infinite permutation is a linear ordering of the set of non-negative integers. Generally, the properties of infinite permutations analogous to those of infinite words show some resemblances and some differences between permutations and…

Combinatorics · Mathematics 2009-11-09 S. V. Avgustinovich , A. E. Frid , T. Kamae , P. V. Salimov

In this paper we extend an earlier result within Dempster-Shafer theory ["Fast Dempster-Shafer Clustering Using a Neural Network Structure," in Proc. Seventh Int. Conf. Information Processing and Management of Uncertainty in Knowledge-Based…

Artificial Intelligence · Computer Science 2016-11-15 Johan Schubert

We provide a complete asymptotic distribution theory for clustered data with a large number of independent groups, generalizing the classic laws of large numbers, uniform laws, central limit theory, and clustered covariance matrix…

Econometrics · Economics 2026-02-03 Bruce E. Hansen , Seojeong Lee

Machines whose main purpose is to permute and sort data are studied. The sets of permutations that can arise are analysed by means of finite automata and avoided pattern techniques. Conditions are given for these sets being enumerated by…

Combinatorics · Mathematics 2007-05-23 M. Albert , M. D. Atkinson , N. Ruskuc

A binary string transmitted via a memoryless i.i.d. deletion channel is received as a subsequence of the original input. From this, one obtains a posterior distribution on the channel input, corresponding to a set of candidate…

Information Theory · Computer Science 2019-03-05 Arash Atashpendar , Marc Beunardeau , Aisling Connolly , Rémi Géraud , David Mestel , A. W. Roscoe , Peter Y. A. Ryan

Genetic and comparative genomic studies indicate that extant genomes are more properly considered to be a fusion product of random mutations over generations and genomic material transfers between individuals of different lineages. This has…

Quantitative Methods · Quantitative Biology 2018-01-16 Andreas D. M. Gunawan , Bingxin Lu , Louxin Zhang

We propose some axioms for hierarchical clustering of probability measures and investigate their ramifications. The basic idea is to let the user stipulate the clusters for some elementary measures. This is done without the need of any…

Machine Learning · Statistics 2016-05-24 Philipp Thomann , Ingo Steinwart , Nico Schmid
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