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» Classifying Problems into Complexity Classes
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105
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ICCV
2003
IEEE
16 years 3 months ago
Minimally-Supervised Classification using Multiple Observation Sets
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...
Chris Stauffer
SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
15 years 2 months ago
Lattice based Clustering of Temporal Gene-Expression Matrices
Individuals show different cell classes when they are in the different stages of a disease, have different disease subtypes, or have different response to a treatment or envir...
Yang Huang, Martin Farach-Colton
119
Voted
JMLR
2010
206views more  JMLR 2010»
14 years 8 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
133
Voted
ICCV
1998
IEEE
15 years 5 months ago
Condensing Image Databases when Retrieval is Based on Non-Metric Distances
One of the key problems in appearance-based vision is understanding how to use a set of labeled images to classify new images. Classification systems that can model human performa...
David W. Jacobs, Daphna Weinshall, Yoram Gdalyahu
90
Voted
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 1 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...