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ICMLA
2010
15 years 4 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...
SIGMOD
2009
ACM
189views Database» more  SIGMOD 2009»
16 years 6 months ago
Query segmentation using conditional random fields
A growing mount of available text data are being stored in relational databases, giving rise to an increasing need for the RDBMSs to support effective text retrieval. In this pape...
Xiaohui Yu, Huxia Shi
RECSYS
2010
ACM
15 years 6 months ago
Nantonac collaborative filtering: a model-based approach
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Toshihiro Kamishima, Shotaro Akaho
BMCBI
2006
173views more  BMCBI 2006»
15 years 6 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy