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» Learning with Rigorous Support Vector Machines
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ANNS
2007
15 years 5 months ago
Direct and indirect classification of high-frequency LNA performance using machine learning techniques
The task of determining low noise amplifier (LNA) high-frequency performance in functional testing is as challenging as designing the circuit itself due to the difficulties associa...
Peter C. Hung, Seán F. McLoone, Magdalena S...
111
Voted
IDEAL
2007
Springer
15 years 10 months ago
Discriminating Microbial Species Using Protein Sequence Properties and Machine Learning
Abstract. Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific ph...
Ali Al-Shahib, David Gilbert, Rainer Breitling
IJCNN
2007
IEEE
15 years 10 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
EDM
2008
136views Data Mining» more  EDM 2008»
15 years 5 months ago
Machine Classification of Peer Comments in Physics
As part of an ongoing project where SWoRD, a Web-based reciprocal peer review system, is used to support disciplinary writing, this study reports machine learning classifications o...
Kwangsu Cho
112
Voted
NIPS
2007
15 years 5 months ago
Bundle Methods for Machine Learning
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le