519 citations · 942 across the 7 of their papers we have counts for
7 papers
IGD Indicator-based Evolutionary Algorithm for Many-objective Optimization Problems
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-object…
Improved Regularity Model-based EDA for Many-objective Optimization
Yanan Sun, Gary G. Yen, Zhang Yi
The performance of multi-objective evolutionary algorithms deteriorates appreciably in solving many-objective optimization problems which encompass more than three objectives. One…
Evolving Unsupervised Deep Neural Networks for Learning Meaningful Representations
Yanan Sun, Gary G. Yen, Zhang Yi
Deep Learning (DL) aims at learning the \emph{meaningful representations}. A meaningful representation refers to the one that gives rise to significant performance improvement of a…
Symmetric low-rank representation for subspace clustering
Jie Chen, Haixian Zhang, Hua Mao +2
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. The…
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification
Xi Peng, Rui Yan, Bo Zhao +2
Spatial Pyramid Matching (SPM) and its variants have achieved a lot of success in image classification. The main difference among them is their encoding schemes. For example, ScSPM…
Subspace clustering using a symmetric low-rank representation
Jie Chen, Hua Mao, Yongsheng Sang +1
In this paper, we propose a low-rank representation with symmetric constraint (LRRSC) method for robust subspace clustering. Given a collection of data points approximately drawn f…
A Unified Framework for Representation-based Subspace Clustering of Out-of-sample and Large-scale Data
Xi Peng, Huajin Tang, Lei Zhang +2
Under the framework of spectral clustering, the key of subspace clustering is building a similarity graph which describes the neighborhood relations among data points. Some recent…