Manifold contraction for semi-supervised classification

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Regularized Semi-supervised Classification on Manifold

Semi-supervised learning gets estimated marginal distribution X P with a large number of unlabeled examples and then constrains the conditional probability ) | ( x y p with a few labeled examples. In this paper, we focus on a regularization approach for semi-supervised classification. The label information graph is first defined to keep the pairwise label relationship and can be incorporated wi...

متن کامل

Manifold-Regularized Selectable Factor Extraction for Semi-supervised Image Classification

Feature selection methods are efficient in modern computer vision applications to reduce the computational cost and the chance of over-fitting. Recently, a novel selectable factor extraction (SFE[3]) framework is proposed to simultaneously perform feature selection and extraction, and is theoretically and practically proved to be effective for high-dimensional data. Although it is advantageous ...

متن کامل

Semi-supervised classification learning by discrimination-aware manifold regularization

Manifold regularization (MR) provides a powerful framework for semi-supervised classification (SSC) using both the labeled and unlabeled data. It first constructs a single Laplacian graph over the whole dataset for representing the manifold structure, and then enforces the smoothness constraint over such graph by a Laplacian regularizer in learning. However, the smoothness over such a single La...

متن کامل

Text Classification Based On Manifold Semi- Supervised Support Vector Machine

This article presents a solution along with experimental results for an application of semi-supervised machine learning techniques and improvement on the SVM (Support Vector Machine) based on geodesic model to build text classification applications for Vietnamese language. The objective here is to improve the semi-supervised machine learning by replacing the kernel function of SVM using geodesi...

متن کامل

Multi-Manifold Semi-Supervised Learning

We study semi-supervised learning when the data consists of multiple intersecting manifolds. We give a finite sample analysis to quantify the potential gain of using unlabeled data in this multi-manifold setting. We then propose a semi-supervised learning algorithm that separates different manifolds into decision sets, and performs supervised learning within each set. Our algorithm involves a n...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Science China Information Sciences

سال: 2010

ISSN: 1674-733X,1869-1919

DOI: 10.1007/s11432-010-0066-0