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» Efficient Discovery of Confounders in Large Data Sets
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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 6 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
KDD
2006
ACM
143views Data Mining» more  KDD 2006»
16 years 6 months ago
Algorithms for discovering bucket orders from data
Ordering and ranking items of different types are important tasks in various applications, such as query processing and scientific data mining. A total order for the items can be ...
Aristides Gionis, Heikki Mannila, Kai Puolamä...
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 6 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
EDBT
2004
ACM
192views Database» more  EDBT 2004»
16 years 6 months ago
LIMBO: Scalable Clustering of Categorical Data
Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
Periklis Andritsos, Panayiotis Tsaparas, Ren&eacut...
ISPAN
1997
IEEE
15 years 10 months ago
A Parallel Pipelined Renderer for Time-Varying Volume Data
This paper presents a strategy for efficiently rendering time-varying volume data on a distributed-memory parallel computer. Visualizing time-varying volume data take both large s...
Tzi-cker Chiueh, Kwan-Liu Ma