SBP
2011
Springer
13 years 7 months ago
2011
Springer
Public health-related topics are difficult to identify in large conversational datasets like Twitter. This study examines how to model and discover public health topics and themes ...
PVLDB
2011
13 years 7 months ago
2011
Matching problems are ubiquitous. They occur in economic markets, labor markets, internet advertising, and elsewhere. In this paper we focus on an application of matching for soci...
ICASSP
2011
IEEE
13 years 9 months ago
2011
IEEE
Recent indexing techniques inspired by source coding have been shown successful to index billions of high-dimensional vectors in memory. In this paper, we propose an approach that ...
IIR
2010
13 years 10 months ago
2010
We present four new feature selection methods for ordinal regression and test them against four different baselines on two large datasets of product reviews.
PC
2007
13 years 12 months ago
2007
Parallel volume rendering is one of the most efficient techniques to achieve real time visualization of large datasets by distributing the data and the rendering process over a c...
BMCBI
2008
14 years 16 days ago
2008
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
BMCBI
2010
14 years 16 days ago
2010
Background: Genome-wide association studies (GWAS) using Copy Number Variation (CNV) are becoming a central focus of genetic research. CNVs have successfully provided target genom...
BMCBI
2010
14 years 16 days ago
2010
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
NIPS
2004
14 years 1 months ago
2004
The computation and memory required for kernel machines with N training samples is at least O(N2 ). Such a complexity is significant even for moderate size problems and is prohibi...
FLAIRS
2001
14 years 1 months ago
2001
Clustering is a discoveringprocess of meaningfulintbrmationby groupingsimilar data into compactclusters. Mostof traditional clustering methodsare in favor of small datasets andhav...