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» Learning Patterns in Noisy Data: The AQ Approach
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COMPLIFE
2006
Springer
15 years 8 months ago
Beating the Noise: New Statistical Methods for Detecting Signals in MALDI-TOF Spectra Below Noise Level
Background: The computer-assisted detection of small molecules by mass spectrometry in biological samples provides a snapshot of thousands of peptides, protein fragments and prote...
Tim O. F. Conrad, Alexander Leichtle, Andre Hageh&...
FAST
2009
15 years 2 months ago
DIADS: Addressing the "My-Problem-or-Yours" Syndrome with Integrated SAN and Database Diagnosis
We present DIADS, an integrated DIAgnosis tool for Databases and Storage area networks (SANs). Existing diagnosis tools in this domain have a database-only (e.g., [11]) or SAN-onl...
Shivnath Babu, Nedyalko Borisov, Sandeep Uttamchan...
ICMLA
2004
15 years 6 months ago
Two new regularized AdaBoost algorithms
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
Yijun Sun, Jian Li, William W. Hager
134
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IJCAI
2007
15 years 6 months ago
Ensembles of Partially Trained SVMs with Multiplicative Updates
The training of support vector machines (SVM) involves a quadratic programming problem, which is often optimized by a complicated numerical solver. In this paper, we propose a muc...
Ivor W. Tsang, James T. Kwok
ICASSP
2011
IEEE
14 years 8 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...