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» Learning Patterns in Noisy Data: The AQ Approach
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ICPR
2008
IEEE
15 years 11 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
RECOMB
2007
Springer
16 years 5 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
155
Voted
MOBICOM
2006
ACM
15 years 10 months ago
Analysis and implications of student contact patterns derived from campus schedules
Characterizing mobility or contact patterns in a campus environment is of interest for a variety of reasons. Existing studies of these patterns can be classified into two basic a...
Vikram Srinivasan, Mehul Motani, Wei Tsang Ooi
159
Voted
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
15 years 2 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim
BIOINFORMATICS
2010
138views more  BIOINFORMATICS 2010»
15 years 4 months ago
Robust unmixing of tumor states in array comparative genomic hybridization data
Motivation: Tumorigenesis is an evolutionary process by which tumor cells acquire sequences of mutations leading to increased growth, invasiveness, and eventually metastasis. It i...
David Tolliver, Charalampos E. Tsourakakis, Ayshwa...