Representing data by sparse combination of contextual data points for classification

06/30/2015
by   Jingyan Wang, et al.
0

In this paper, we study the problem of using contextual da- ta points of a data point for its classification problem. We propose to represent a data point as the sparse linear reconstruction of its context, and learn the sparse context to gather with a linear classifier in a su- pervised way to increase its discriminative ability. We proposed a novel formulation for context learning, by modeling the learning of context reconstruction coefficients and classifier in a unified objective. In this objective, the reconstruction error is minimized and the coefficient spar- sity is encouraged. Moreover, the hinge loss of the classifier is minimized and the complexity of the classifier is reduced. This objective is opti- mized by an alternative strategy in an iterative algorithm. Experiments on three benchmark data set show its advantage over state-of-the-art context-based data representation and classification methods.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/09/2016

Supervised multiview learning based on simultaneous learning of multiview intact and single view classifier

Multiview learning problem refers to the problem of learning a classifie...
research
07/31/2015

A novel multivariate performance optimization method based on sparse coding and hyper-predictor learning

In this paper, we investigate the problem of optimization multivariate p...
research
11/26/2013

Semi-Supervised Sparse Coding

Sparse coding approximates the data sample as a sparse linear combinatio...
research
02/26/2016

Shape-aware Surface Reconstruction from Sparse 3D Point-Clouds

The reconstruction of an object's shape or surface from a set of 3D poin...
research
04/11/2016

Semi-supervised learning of local structured output predictors

In this paper, we study the problem of semi-supervised structured output...
research
12/24/2013

3D Interest Point Detection via Discriminative Learning

The task of detecting the interest points in 3D meshes has typically bee...

Please sign up or login with your details

Forgot password? Click here to reset