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== Introduction and problem motivation ==
== Introduction and problem motivation ==
In classification problems, kernel methods are used for pattern analysis and require only user-specified kernel. Kernel methods can be thought of as instance-based methods where they learn the i-th training examples are "remembered" to learn for corresponding weights. Prediction on untrained examples are then treated with a similarity function, k (also called a kernel between this untrained example and each of the training inputs. In short, a similarity function measures similarity between two objects. An example of a kernel method is the support vector machine.
In classification problems, kernel methods are used for pattern analysis and require only user-specified kernel. Kernel methods can be thought of as instance-based methods where they learn the i-th training examples are "remembered" to learn for corresponding weights. Prediction on untrained examples are then treated with a similarity function, k (also called a kernel between this untrained example and each of the training inputs. In short, a similarity function measures similarity between two objects.  
By conventional notation, we have that
 
<\math> \alpha <math>
 
An example of a kernel method is the support vector machine. These methids

Revision as of 10:34, 7 March 2018

Random features for large scale kernel machines

Group members

Faith Lee

Jacov Lisulov

Shiwei Gong

Introduction and problem motivation

In classification problems, kernel methods are used for pattern analysis and require only user-specified kernel. Kernel methods can be thought of as instance-based methods where they learn the i-th training examples are "remembered" to learn for corresponding weights. Prediction on untrained examples are then treated with a similarity function, k (also called a kernel between this untrained example and each of the training inputs. In short, a similarity function measures similarity between two objects. By conventional notation, we have that

<\math> \alpha <math>

An example of a kernel method is the support vector machine. These methids