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Experience with a clustered parallel reduction machine

M Beemster, P.H Hartel, L.O Hertzberger, R.F.H Hofman, K.G Langendoen, L.L Li, R Milikowski, WG Vree, H.P Barendregt, J.C Mulder
1993 Future generations computer systems  
A clustered architecture has been designed to exploit divide and conquer parallelism in functional programs.  ...  A special processor for graph reduction has been designed as a basic building block for the machine. A prototype of a single cluster machine has been constructed with stock hardware.  ...  Acknowledgements We thank Henk Muller and the two referees for their comments on a draft version of the paper. The support of the European Institute for Technology under grant no.  ... 
doi:10.1016/0167-739x(93)90011-d fatcat:ank45yd6czgm5hmbfoaqws33mm

A Clustered Gaussian Process Model for Computer Experiments

Chih-Li Sung, Benjamin Haaland, Youngdeok Hwang, Siyuan Lu
2023 Statistica sinica  
In this article, we propose a clustered Gaussian process model which simultaneously segments the input data into multiple clusters and fits a Gaussian process model in each.  ...  In our simulations as well as a real application to solar irradiance emulation, our proposed method has smaller mean squared errors than its main competitors, with competitive computation time, and provides  ...  Moreover, the flexible structure of the proposed model can be easily generalized to other applications in computer experiments.  ... 
doi:10.5705/ss.202020.0456 fatcat:wxqt5l4sibgotpl6ztuzlrkweq

Hierarchical Cluster Analysis of a Convection-Allowing Ensemble during the Hazardous Weather Testbed 2009 Spring Experiment. Part II: Ensemble Clustering over the Whole Experiment Period

Aaron Johnson, Xuguang Wang, Ming Xue, Fanyou Kong
2011 Monthly Weather Review  
There is an increasing impact of the planetary boundary layer (PBL) scheme on clustering relative to the microphysics scheme at later lead times.  ...  At early lead times (3 h, valid at 0300 UTC) precipitation forecasts cluster primarily by data assimilation and model dynamic core, indicating a dominating impact of models, with secondary clustering by  ...  Composite dendrograms Hierarchical clustering is displayed graphically as a dendrogram, showing the step-by-step merging of clusters.  ... 
doi:10.1175/mwr-d-11-00016.1 fatcat:tisnsupcg5dk7eg45oxring6ie

A new algorithm for clustering search results

Giansalvatore Mecca, Salvatore Raunich, Alessandro Pappalardo
2007 Data & Knowledge Engineering  
Moreover, the algorithm is such that the SVD computation step has in practice good performance, which makes it feasible to perform clustering when term vectors are available.  ...  We show that the algorithm has very good classification performance, and that it can be effectively used to cluster results of a search engine to make them easier to browse by users.  ...  Indexing Scheme We are now ready to discuss a number of experimental evidences. As a first step, we dealt with the problem of selecting the correct weighting scheme.  ... 
doi:10.1016/j.datak.2006.10.006 fatcat:fqullx3x7jgmpny3c4hap5kg6y

Maximum volume clustering: a new discriminative clustering approach

Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama
2013 Journal of machine learning research  
In this paper, we introduce a new discriminative clustering model based on the large volume principle called maximum volume clustering (MVC), and then propose two approximation schemes to solve this MVC  ...  The optimization involved in hardlabel MVC is convex, and under mild conditions, the optimization involved in soft-label MVC is akin to a convex one in terms of the resulting clusters.  ...  An SQP constructs and solves a local QP at each iteration, yielding a step toward the optimum.  ... 
dblp:journals/jmlr/NiuDSS13 fatcat:cvo43atwwfdo7mupp452uskocu

Quartile Clustering: A quartile based technique for Generating Meaningful Clusters [article]

Saptarsi Goswami, Amlan Chakrabarti
2012 arXiv   pre-print
However these definitions fail to attach a clear meaning/semantics to the generated clusters.  ...  On the samepremise, we propose our new algorithm named as quartile clustering technique. Through a series of experiments we establish efficacy of this algorithm.  ...  As the first step, we map each at- This is a parametric method where each cluster corre- tribute of each observation to a literal Q1, Q2, Q3, Q4 or H1, sponds to a Gaussian distribution  ... 
arXiv:1203.4157v1 fatcat:fhbphlsrgbcttksk5sjuz7wbay

Word Clustering as a Feature for Arabic Sentiment Classification

Saud Alotaibi, Charles Anderson
2017 International Journal of Education and Management Engineering  
Our proposed method employs supervised sentiment classification by enriching the feature space model with word cluster information.  ...  In addition, the experiments and evaluations that were conducted in this study demonstrated that by combining the clustering feature with sentiment analysis for Arabic, this improved the performance of  ...  In the first step to this feature, there is a requirement to create a cluster from the given text.  ... 
doi:10.5815/ijeme.2017.01.01 fatcat:ku6druqjing5fhq4bcje2335ge

VQ-agglomeration: a novel approach to clustering

J.-H. Wang, J.-D. Rau
2001 IEE Proceedings - Vision Image and Signal Processing  
A novel approach called 'VQ-agglomeration' capable of performing fast and autonomous clustering is presented.  ...  Each codeword is associated with a gravisphere that has a well defined attraction radius.  ...  In fact, a too large Mf not only incurs more computational time, it may also causes erroneous clusters. Thus, we present a recursive scheme to solve this problem of guessing Mf blindly.  ... 
doi:10.1049/ip-vis:20010139 fatcat:d7l5fac5wjatvdxls4uhngk22y

The Clustered Dial-a-Ride Problem

Fabian Feitsch, Sabine Storandt
2019 International Conference on Automated Planning and Scheduling  
To make use of this observation, we devise a classification algorithm which can decide whether the optimal route exhibits these structural properties before computing it.  ...  In this paper, we consider the clustered dial-a-ride problem, where we do not operate on a complete graph but on a graph composed of serially numbered cliques where each clique is connected to the next  ...  Step 2 covers all costs generated inside the cluster C i . To this end, for every S ∈ S we compute the initial and final state vector of all rides before serving S and afterwards.  ... 
dblp:conf/aips/FeitschS19 fatcat:pyewzphspnd3zctgqe3q3c4q6i

HG-means: A scalable hybrid genetic algorithm for minimum sum-of-squares clustering

Daniel Gribel, Thibaut Vidal
2019 Pattern Recognition  
This may be related to differences of computational effort, or to the assumption that a near-optimal solution of the MSSC has only a marginal impact on clustering validity.  ...  Minimum sum-of-squares clustering (MSSC) is a widely used clustering model, of which the popular K-means algorithm constitutes a local minimizer.  ...  Experimental Analysis We conducted extensive computational experiments to evaluate the performance of HG-means.  ... 
doi:10.1016/j.patcog.2018.12.022 fatcat:nvtkdgmwh5gylizgydgqa2dj3u

A Survey: Clustering Ensembles Techniques

Reza Ghaemi, Md. Nasir Sulaiman, Hamidah Ibrahim, Norwati Mustapha
2009 Zenodo  
The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution.  ...  Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions.  ...  SPEC can be simply described as a graph G = (V,W), it first computes the degree matrix D, which is a diagonal matrix such that D(i, i) = ∑ j W(i, j).  ... 
doi:10.5281/zenodo.1329276 fatcat:h65gdbhmbnf4tnrycigmdzv3w4

A comparison of clustering algorithms applied to color image quantization

P. Scheunders
1997 Pattern Recognition Letters  
The hierarchical clustering scheme is shown to obtain near-global optimal results with low computational load.  ...  In this paper color image quantization by clustering is discussed. A clustering scheme, based on competitive learning is constructed and compared to the well-known C-means clustering algorithm.  ...  This scheme will be compared to CMA, CL and the genetic approach, with respect to optimality and computation time.  ... 
doi:10.1016/s0167-8655(97)00116-5 fatcat:bhttict5s5btvnoriuwbsuoqve

A review of clustering techniques and developments

Amit Saxena, Mukesh Prasad, Akshansh Gupta, Neha Bharill, Om Prakash Patel, Aruna Tiwari, Meng Joo Er, Weiping Ding, Chin-Teng Lin
2017 Neurocomputing  
This paper presents a comprehensive study on clustering: exiting methods and developments made at various times.  ...  There are different methods for clustering the objects such as hierarchical, partitional, grid, density based and model based.  ...  Compute the first k generalized eigenvectors u1, . . . , uk of the generalized eigen problem Lu = λDu. 5. Let U ∈ R n×k be the matrix containing the vectors u1, . . . , uk as columns. 6.  ... 
doi:10.1016/j.neucom.2017.06.053 fatcat:z2yzjsdwgnbzbam5bg3s4lu6ny

Creating a Cluster Hierarchy under Constraints of a Partially Known Hierarchy [chapter]

Korinna Bade, Andreas Nürnberger
2008 Proceedings of the 2008 SIAM International Conference on Data Mining  
Major issues of current approaches to constraint based clustering are discussed, especially towards the hierarchical setting.  ...  Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered.  ...  Therefore, we reduce the number of generated constraints by first clustering similar items.  ... 
doi:10.1137/1.9781611972788.2 dblp:conf/sdm/BadN08 fatcat:2efx2etdj5ex5hpzgqcqfaqjye

OLAP Query Evaluation in a Database Cluster: A Performance Study on Intra-Query Parallelism [chapter]

Fuat Akal, Klemens Böhm, Hans-Jörg Schek
2002 Lecture Notes in Computer Science  
We run extensive experiments to evaluate these query classes in quantitative terms. Our results are an important step towards a two-phase query optimizer.  ...  In the first phase, the coordination infrastructure decomposes a query into subqueries and ships them to appropriate cluster nodes.  ...  Within this general framework, this paper is a first step to address the following specific questions. 1. How well can we parallelize a given query?  ... 
doi:10.1007/3-540-45710-0_18 fatcat:tem2be3ihvfj7ojgzjlt57h4w4
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