Results 21 to 30 of about 31,009 (261)
Increments of Random Partitions [PDF]
Combinatorics, Probability and Computing, 2006 For any partition of $\{1, 2, ..., n\}$ we define its {\it increments} $X_i, 1 \le i \le n$ by $X_i = 1$ if $i$ is the smallest element in the partition block that contains it, $X_i = 0$ otherwise. We prove that for partially exchangeable random partitions (where the probability of a partition depends only on its block sizes in order of appearance ...
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Differentiable Random Partition Models
Advances in Neural Information Processing Systems 36, 2023 Partitioning a set of elements into an unknown number of mutually exclusive subsets is essential in many machine learning problems. However, assigning elements, such as samples in a dataset or neurons in a network layer, to an unknown and discrete number of subsets is inherently non-differentiable, prohibiting end-to-end gradient-based optimization of ...
Thomas M. Sutter +3 more
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Partition optimization for a random process realization to estimate its expected value [PDF]
Serbian Journal of Electrical Engineering, 2017 The paper provides an analytical proof the optimal number of partitions of a non-stationary random process realization, which is necessary for estimating its expected value when using “the estimation reproduction” method for signal processing ...
Marchuk Vladimir +4 more
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Two-Level-Oriented Selective Clustering Ensemble Based on Hybrid Multi-Modal Metrics
IEEE Access, 2018 The purpose of selective clustering ensemble is to select a subset of base clustering partitions with predictive performance and combine these partitions into more accurate and stable final results.
Hongling Wang, Gang Liu
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Mixture of Species Sampling Models
Mathematics, 2021 We introduce mixtures of species sampling sequences (mSSS) and discuss how these sequences are related to various types of Bayesian models. As a particular case, we recover species sampling sequences with general (not necessarily diffuse) base measures ...
Federico Bassetti, Lucia Ladelli
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K-MEANS WITH SAMPLING FOR DETERMINING PROMINENT COLORS IN IMAGES
ICTACT Journal on Soft Computing, 2022 A tool that quickly calculates the dominant colors of an image can be very useful in image processing. The k-means clustering algorithm has this potential since it partitions a set of data into n clusters and returns a representative data point from each
Angelina Cheng +2 more
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Complex Network Statistics to the Design of Fire Breaks for the Control of Fire Spreading
Chemical Engineering Transactions, 2015 A computational approach for identifying efficient fuel breaks partitions for the containment of fire incidents in forests is proposed. The approach is based on the complex networks statistics, namely the centrality measures and cellular automata ...
L. Russo +3 more
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Asymptotics of Smallest Component Sizes in Decomposable Combinatorial Structures of Alg-Log Type [PDF]
Discrete Mathematics & Theoretical Computer Science, 2010 A decomposable combinatorial structure consists of simpler objects called components which by thems elves cannot be further decomposed. We focus on the multi-set construction where the component generating function C(z) is of alg-log type, that is, C(z ...
Li Dong +3 more
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Relative cluster entropy for power-law correlated sequences
SciPost Physics, 2022 We propose an information-theoretical measure, the \textit{relative cluster entropy} $\mathcal{D_{C}}[P \| Q] $, to discriminate among cluster partitions characterised by probability distribution functions $P$ and $Q$.
Anna Carbone, Linda Ponta
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Demand Models With Random Partitions [PDF]
Journal of the American Statistical Association, 2018 Many economic models of consumer demand require researchers to partition sets of products or attributes prior to the analysis. These models are common in applied problems when the product space is large or spans multiple categories. While the partition is traditionally fixed a priori, we let the partition be a model parameter and propose a Bayesian ...
Adam N. Smith, Greg M. Allenby
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