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DMIN
2006
142views Data Mining» more  DMIN 2006»
9 years 9 months ago
Parallel Hybrid Clustering using Genetic Programming and Multi-Objective Fitness with Density (PYRAMID)
Clustering is the process of locating patterns in large data sets. It is an active research area that provides value to scientific as well as business applications. Practical clust...
Junping Sun, William Sverdlik, Samir Tout
CASCON
2006
210views Education» more  CASCON 2006»
9 years 9 months ago
Accelerating marching cubes with graphics hardware
For large data sets in medicine and science, efficient isosurface extraction and rendering is crucial for interactive visualization. Previous GPU acceleration techniques have been...
Gunnar Johansson, Hamish Carr
EMNLP
2008
9 years 9 months ago
A comparison of Bayesian estimators for unsupervised Hidden Markov Model POS taggers
There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of t...
Jianfeng Gao, Mark Johnson
EMNLP
2007
9 years 9 months ago
Large Language Models in Machine Translation
This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 t...
Thorsten Brants, Ashok C. Popat, Peng Xu, Franz Jo...
DMIN
2008
176views Data Mining» more  DMIN 2008»
9 years 9 months ago
Multi-Class SVM for Large Data Sets Considering Models of Classes Distribution
Support Vector Machines (SVM) have gained profound interest amidst the researchers. One of the important issues concerning SVM is with its application to large data sets. It is rec...
Jair Cervantes, Xiaoou Li, Wen Yu
COMAD
2008
9 years 9 months ago
Discovering Interesting Subsets Using Statistical Analysis
In this paper we present algorithms for identifying interesting subsets of a given database of records. In many real life applications, it is important to automatically discover s...
Maitreya Natu, Girish Palshikar
APVIS
2007
9 years 9 months ago
Interpreting large visual similarity matrices
Visual similarity matrices (VSMs) are a common technique for visualizing graphs and other types of relational data. While traditionally used for small data sets or well-ordered la...
Christopher Mueller, Benjamin Martin, Andrew Lumsd...
APVIS
2010
9 years 9 months ago
GMap: Visualizing graphs and clusters as maps
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
Emden R. Gansner, Yifan Hu, Stephen G. Kobourov
AMW
2010
9 years 9 months ago
Run-time Optimization for Pipelined Systems
Traditional optimizers fail to pick good execution plans, when faced with increasingly complex queries and large data sets. This failure is even more acute in the context of XQuery...
Riham Abdel Kader, Maurice van Keulen, Peter A. Bo...
VVS
1995
IEEE
132views Visualization» more  VVS 1995»
9 years 11 months ago
Multi-Dimensional Trees for Controlled Volume Rendering and Compression
This paper explores the use of multi-dimensional trees to provide spatial and temporal e ciencies in imaging large data sets. Each node of the tree contains a model of the data in...
Jane Wilhelms, Allen Van Gelder
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