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Kernel perceptron

Known as: Forgetron 
In machine learning, the kernel perceptron is a variant of the popular perceptron learning algorithm that can learn kernel machines, i.e. non-linear… 
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Related topics

Related topics

13 relations
Active set methodBasis functionDuality (optimization)Kernel method

Broader (1)

Statistical classification

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2016
Review
2016
Kernel Affine Projection Algorithm
The unknown system to be identified by an adaptive filter is usually assumed to be a linear system. Based on this assumption, we… 
2013
2013
An importance weighted projection method for incremental learning under unstationary environments
In this paper, we propose a new projection method for incremental learning on a fixed number of kernels. If the number of the… 
2010
2010
Fast weight calculation for kernel-based perceptron in two-class classification problems
We propose a method, called Direct Kernel Perceptron (DKP), to directly calculate the weights of a single perceptron using a… 
2009
2009
Learning to rank with a novel kernel perceptron method
While conventional ranking algorithms, such as the PageRank, rely on the web structure to decide the relevancy of a web page… 
2009
2009
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life… 
Review
2009
Review
2009
Online Learning for URL classification
This work consists of a review of online algorithms for URL classification followed by some extensions and tweaking of these… 
2005
2005
A multiclass kernel perceptron algorithm
Original kernel machines (e.g., support vector machine, least squares support vector machine, kernel Fisher discriminant analysis… 
2004
2004
Visual Kernel Perceptron
In this paper the novel classification algorithm based on visual kernel perceptron is presented. The proposed method first maps… 
2003
2003
Feature Extraction Languages for Propositionalized Relational Learning
We study representations and relational learning over structured domains within a propositionalization framework that decouples… 
2002
2002
Learning Kernel Classifiers - Theory and Algorithms
  • Ralf Herbrich
  • Adaptive computation and machine learning
  • 2002
  • Corpus ID: 263879802
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