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ICMLA
2010
14 years 8 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
AUSDM
2008
Springer
229views Data Mining» more  AUSDM 2008»
15 years 12 hour ago
Minors as Miners - Modelling and Evaluating Ontological and Linguistic Learning
Growing up is in large measure learning about the world and our social and linguistic environment. We might call this data mining, although it is far more multimodal and immersive...
David M. W. Powers
TCBB
2011
14 years 5 months ago
Data Mining on DNA Sequences of Hepatitis B Virus
: Extraction of meaningful information from large experimental datasets is a key element of bioinformatics research. One of the challenges is to identify genomic markers in Hepatit...
Kwong-Sak Leung, Kin-Hong Lee, Jin Feng Wang, Eddi...
SIGKDD
2000
103views more  SIGKDD 2000»
14 years 9 months ago
Interface '99: A Data Mining Overview
This personal overview of Interface '99 is intended to communicate its meaning and relevance to SIGKDD, as well as provide valuable information on trends within the Interface...
Arnold Goodman
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
15 years 10 months ago
Anomaly pattern detection in categorical datasets
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
Kaustav Das, Jeff G. Schneider, Daniel B. Neill