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» Using Machine Learning Techniques to Interpret WH-questions
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ICML
2000
IEEE
16 years 2 months ago
Duality and Geometry in SVM Classifiers
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
Kristin P. Bennett, Erin J. Bredensteiner
IJCAI
2007
15 years 2 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell
DATAMINE
2002
147views more  DATAMINE 2002»
15 years 1 months ago
Discretization: An Enabling Technique
Discrete values have important roles in data mining and knowledge discovery. They are about intervals of numbers which are more concise to represent and specify, easier to use and ...
Huan Liu, Farhad Hussain, Chew Lim Tan, Manoranjan...
AAI
1998
101views more  AAI 1998»
15 years 1 months ago
Layered Approach to Learning Client Behaviors in the Robocup Soccer Server
In the past few years, Multiagent Systems (MAS) has emerged as an active subfield of Artificial Intelligence (AI). Because of the inherent complexity of MAS, there is much inter...
Peter Stone, Manuela M. Veloso
ML
2008
ACM
15 years 1 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen