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Linear1 Support Vector Machines (e.g., SVMperf, Pegasos, LIBLINEAR) are powerful and extremely efficient classification tools when the datasets are very large and/or highdimensional, which is commo...
We consider the problem of learning a binary classifier from a training set of positive and unlabeled examples, both in the inductive and in the transductive setting. This problem, often referred to a...
Support Vector Machine (SVM) is a popular classification paradigm in machine learning and has achieved great success in real applications. However, the standard SVM can not select variables automatica...
This note proposes a new methodology for function classification with Support Vector Machine (SVM). Rather than relying on projection on a truncated Hilbert basis as in our previous work, we use an im...

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