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» Geometric Neural Networks and Support Multi-Vector Machines
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COLT
2001
Springer
15 years 2 months ago
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
Peter L. Bartlett, Shahar Mendelson
145
Voted

Book
640views
16 years 8 months ago
Introduction to Pattern Recognition
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typical...
Sargur Srihari
JUCS
2008
136views more  JUCS 2008»
14 years 9 months ago
Crime Scene Representation (2D, 3D, Stereoscopic Projection) and Classification
: In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be u...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...
82
Voted
TIT
2002
164views more  TIT 2002»
14 years 9 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
67
Voted
ICANN
2009
Springer
15 years 2 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola