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» Input Modeling Using Quantile Statistical Methods
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BMCBI
2007
134views more  BMCBI 2007»
13 years 10 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
NIPS
2007
13 years 11 months ago
Neural characterization in partially observed populations of spiking neurons
Point process encoding models provide powerful statistical methods for understanding the responses of neurons to sensory stimuli. Although these models have been successfully appl...
Jonathan Pillow, Peter E. Latham
ISNN
2009
Springer
14 years 4 months ago
A New Instance-Based Label Ranking Approach Using the Mallows Model
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Weiwei Cheng, Eyke Hüllermeier
IPMI
2005
Springer
14 years 11 months ago
Multi-figure Anatomical Objects for Shape Statistics
Abstract. Multi-figure m-reps allow us to represent and analyze a complex anatomical object by its parts, by relations among its parts, and by the object itself as a whole entity. ...
Qiong Han, Stephen M. Pizer, Derek Merck, Sarang C...
TCSV
2008
124views more  TCSV 2008»
13 years 10 months ago
A Novel Look-Up Table Design Method for Data Hiding With Reduced Distortion
Look-up table (LUT)-based data hiding is a simple and efficient technique to hide secondary information (watermark) into multimedia work for various applications such as copyright ...
Xiao-Ping Zhang, Kan Li, Xiaofeng Wang