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Support Vector Machines,Kernel Logistic Regression,and Boosting
Support Vector Machines Kernel Logistic Regression Boosting
2015/8/21
Support Vector Machines,Kernel Logistic Regression,and Boosting.
Mean field variational Bayesian inference for support vector machine classification
Approximate Bayesian inference variable selection missing data mixed model Markov chain Monte Carlo
2013/6/14
A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented. This representation allows circumvention of ma...
Complex Support Vector Machines for Regression and Quaternary Classification
Support Vector Machines Kernel methods Widely linear estimation com-plex data
2013/4/28
We present a support vector machines (SVM) rationale suitable for regression and quaternary classification problems that use complex data, exploiting the notions of widely linear estimation and pure c...
An Equivalence between the Lasso and Support Vector Machines
Equivalence the Lasso Support Vector Machines
2013/4/28
We investigate the relation of two fundamental tools in machine learning, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resu...
Nonsmooth Formulation of the Support Vector Machine for a Neural Decoding Problem
Optimization and Control (math.OC) Numerical Analysis (math.NA) Statistics Theory (math.ST)
2010/12/17
This paper formulates a generalized classification algorithm with an application to classifying (or `decoding') neural activity in the brain. Medical doctors and researchers have long been interested ...
Asymptotic Normality of Support Vector Machines for Classification and Regression
Nonparametric regression support vector machines asymptotic normality
2010/10/14
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
Structured variable selection in support vector machines
Classification Heredity Nonparametric estimation Support vector machine Variable selection
2009/9/16
When applying the support vector machine (SVM) to high-dimensional classification problems, we often impose a sparse structure in the SVM to eliminate the influences of the irrelevant predictors. The ...
Consistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noise
Observational noise model forecasting dynamical systems support vector machines consistency
2010/4/30
We consider the problem of forecasting the next (observable)
state of an unknown ergodic dynamical system from a noisy observation
of the present state. Our main result shows, for example, that
sup...
Support vector machine for functional data classification
Functional Data Analysis Support Vector Machine Classification Consistency
2010/4/29
In many applications, input data are sampled functions taking their values in infinite
dimensional spaces rather than standard vectors. This fact has complex consequences
on data analysis algorithms...