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» Using Goal-Models to Analyze Variability
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BMCBI
2008
92views more  BMCBI 2008»
13 years 9 months ago
A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles
Background: The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI) and ...
Samiran Ghosh, David F. Grant, Dipak K. Dey, Denni...
ICFP
2004
ACM
14 years 8 months ago
Types, potency, and idempotency: why nonlinearity and amnesia make a type system work
Useful type inference must be faster than normalization. Otherwise, you could check safety conditions by running the program. We analyze the relationship between bounds on normali...
Harry G. Mairson, Peter Møller Neergaard
CVPR
2004
IEEE
14 years 10 months ago
On the Distribution of Saliency
The calculation of salient structures is one of the early and basic ideas of perceptual organization in Computer Vision. Saliency algorithms typically mark edge-points with some s...
Alexander Berengolts, Michael Lindenbaum
ECCV
2008
Springer
14 years 10 months ago
Background Subtraction on Distributions
Environmental monitoring applications present a challenge to current background subtraction algorithms that analyze the temporal variability of pixel intensities, due to the comple...
Teresa Ko, Stefano Soatto, Deborah Estrin
ICML
2009
IEEE
14 years 9 months ago
Learning dictionaries of stable autoregressive models for audio scene analysis
In this paper, we explore an application of basis pursuit to audio scene analysis. The goal of our work is to detect when certain sounds are present in a mixed audio signal. We fo...
Youngmin Cho, Lawrence K. Saul