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SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
13 years 11 months ago
Predictive Modeling with Heterogeneous Sources
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
13 years 11 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
SDM
2008
SIAM
122views Data Mining» more  SDM 2008»
13 years 11 months ago
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu
SOFTWARE
2002
13 years 9 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
ICMLA
2010
13 years 7 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...