Search Results for author: Zhang Yi

Found 16 papers, 0 papers with code

IGD Indicator-based Evolutionary Algorithm for Many-objective Optimization Problems

no code implementations24 Feb 2018 Yanan Sun, Gary G. Yen, Zhang Yi

Inverted Generational Distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multi- and many-objective evolutionary algorithms.

Improved Regularity Model-based EDA for Many-objective Optimization

no code implementations24 Feb 2018 Yanan Sun, Gary G. Yen, Zhang Yi

Finally, by assigning the Pareto-optimal solutions to the uniformly distributed reference vectors, a set of solutions with excellent diversity and convergence is obtained.

Dimensionality Reduction

Evolving Unsupervised Deep Neural Networks for Learning Meaningful Representations

no code implementations13 Dec 2017 Yanan Sun, Gary G. Yen, Zhang Yi

Specifically, error classification rate on MNIST with $1. 15\%$ is reached by the proposed algorithm consistently, which is a very promising result against state-of-the-art unsupervised DL algorithms.

General Classification

Deep Sparse Subspace Clustering

no code implementations25 Sep 2017 Xi Peng, Jiashi Feng, Shijie Xiao, Jiwen Lu, Zhang Yi, Shuicheng Yan

In this paper, we present a deep extension of Sparse Subspace Clustering, termed Deep Sparse Subspace Clustering (DSSC).

Long Concept Query on Conceptual Taxonomies

no code implementations29 Nov 2015 Zhang Yi, Xiao Yanghua, Hwang Seung-won, Wang Wei

However, as such increase of recall often invites false positives and decreases precision in return, we propose the following two techniques: First, we identify concepts with different relatedness to generate linear orderings and pairwise ordering constraints.

Entity Retrieval

Connections Between Nuclear Norm and Frobenius Norm Based Representations

no code implementations26 Feb 2015 Xi Peng, Can-Yi Lu, Zhang Yi, Huajin Tang

A lot of works have shown that frobenius-norm based representation (FNR) is competitive to sparse representation and nuclear-norm based representation (NNR) in numerous tasks such as subspace clustering.

Automatic Subspace Learning via Principal Coefficients Embedding

no code implementations17 Nov 2014 Xi Peng, Jiwen Lu, Zhang Yi, Rui Yan

In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i. e., automatic subspace learning), and 2) how to learn the underlying subspace in the presence of Gaussian noise (i. e., robust subspace learning).

Symmetric low-rank representation for subspace clustering

no code implementations31 Oct 2014 Jie Chen, Haixian Zhang, Hua Mao, Yongsheng Sang, Zhang Yi

We propose a symmetric low-rank representation (SLRR) method for subspace clustering, which assumes that a data set is approximately drawn from the union of multiple subspaces.

Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification

no code implementations22 Sep 2014 Xi Peng, Rui Yan, Bo Zhao, Huajin Tang, Zhang Yi

Although the methods achieve a higher recognition rate than the traditional SPM, they consume more time to encode the local descriptors extracted from the image.

Classification General Classification +2

Subspace clustering using a symmetric low-rank representation

no code implementations7 Mar 2014 Jie Chen, Hua Mao, Yongsheng Sang, Zhang Yi

In this paper, we propose a low-rank representation with symmetric constraint (LRRSC) method for robust subspace clustering.

A Unified Framework for Representation-based Subspace Clustering of Out-of-sample and Large-scale Data

no code implementations25 Sep 2013 Xi Peng, Huajin Tang, Lei Zhang, Zhang Yi, Shijie Xiao

In this paper, we propose a unified framework which makes representation-based subspace clustering algorithms feasible to cluster both out-of-sample and large-scale data.

Scalable Sparse Subspace Clustering

no code implementations CVPR 2013 Xi Peng, Lei Zhang, Zhang Yi

To address the problems, this paper proposes out-of-sample extension of SSC, named as Scalable Sparse Subspace Clustering (SSSC), which makes SSC feasible to cluster large scale data sets.

Motion Segmentation Online Clustering

Locally linear representation for image clustering

no code implementations24 Apr 2013 Liangli Zhen, Zhang Yi, Xi Peng, Dezhong Peng

There are two popular schemes to construct a similarity graph, i. e., pairwise distance based scheme and linear representation based scheme.

Image Clustering

Learning Locality-Constrained Collaborative Representation for Face Recognition

no code implementations4 Oct 2012 Xi Peng, Lei Zhang, Zhang Yi, Kok Kiong Tan

The model of low-dimensional manifold and sparse representation are two well-known concise models that suggest each data can be described by a few characteristics.

Dimensionality Reduction Face Recognition

Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering

no code implementations5 Sep 2012 Xi Peng, Zhiding Yu, Huajin Tang, Zhang Yi

Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors and retains only connections between the data points from the same subspace (i. e., intra-subspace data points).

Image Clustering Motion Segmentation

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