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» Data Mining via Support Vector Machines
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TKDE
2010
182views more  TKDE 2010»
14 years 8 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
BIODATAMINING
2008
163views more  BIODATAMINING 2008»
14 years 10 months ago
Multivariate profiling of neurodegeneration-associated changes in a subcellular compartment of neurons via image processing
Background: Dysfunction in the endolysosome, a late endosomal to lysosomal degradative intracellular compartment, is an early hallmark of some neurodegenerative diseases, in parti...
Saravana K. Kumarasamy, Yunshi Wang, Vignesh Viswa...
TLDI
2003
ACM
110views Formal Methods» more  TLDI 2003»
15 years 3 months ago
Type-safe multithreading in cyclone
We extend Cyclone, a type-safe polymorphic language at vel of abstraction, with threads and locks. Data races can violate type safety in Cyclone. An extended type system staticall...
Dan Grossman
ICML
2007
IEEE
15 years 11 months ago
Direct convex relaxations of sparse SVM
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...
PR
2007
165views more  PR 2007»
14 years 9 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch