Search Results for author: Chong Peng

Found 28 papers, 10 papers with code

Explainable Censored Learning: Finding Critical Features with Long Term Prognostic Values for Survival Prediction

no code implementations30 Sep 2022 Xinxing Wu, Chong Peng, Richard Charnigo, Qiang Cheng

Interpreting critical variables involved in complex biological processes related to survival time can help understand prediction from survival models, evaluate treatment efficacy, and develop new therapies for patients.

Survival Prediction

Alcohol Intake Differentiates AD and LATE: A Telltale Lifestyle from Two Large-Scale Datasets

no code implementations25 Aug 2022 Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng

Alzheimer's disease (AD), as a progressive brain disease, affects cognition, memory, and behavior.

PRIME: Uncovering Circadian Oscillation Patterns and Associations with AD in Untimed Genome-wide Gene Expression across Multiple Brain Regions

1 code implementation25 Aug 2022 Xinxing Wu, Chong Peng, Gregory Jicha, Donna Wilcock, Qiang Cheng

Then, we apply it to study oscillation patterns in untimed genome-wide gene expression from 19 human brain regions of controls and AD patients.

A Novel Long-term Iterative Mining Scheme for Video Salient Object Detection

no code implementations20 Jun 2022 Chenglizhao Chen, Hengsen Wang, Yuming Fang, Chong Peng

The existing state-of-the-art (SOTA) video salient object detection (VSOD) models have widely followed short-term methodology, which dynamically determines the balance between spatial and temporal saliency fusion by solely considering the current consecutive limited frames.

object-detection Salient Object Detection +1

Log-based Sparse Nonnegative Matrix Factorization for Data Representation

no code implementations22 Apr 2022 Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng

Nonnegative matrix factorization (NMF) has been widely studied in recent years due to its effectiveness in representing nonnegative data with parts-based representations.

Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization

no code implementations8 Jan 2022 Chong Peng, Yang Liu, Yongyong Chen, Xinxin Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng

In this paper, we propose a novel nonconvex approach to robust principal component analysis for HSI denoising, which focuses on simultaneously developing more accurate approximations to both rank and column-wise sparsity for the low-rank and sparse components, respectively.

Hyperspectral Image Denoising Image Denoising

Kernel Two-Dimensional Ridge Regression for Subspace Clustering

no code implementations3 Nov 2020 Chong Peng, Qian Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng

It directly uses 2D data as inputs such that the learning of representations benefits from inherent structures and relationships of the data.

regression

Structured Graph Learning for Clustering and Semi-supervised Classification

no code implementations31 Aug 2020 Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian

Furthermore, most existing graph-based methods conduct clustering and semi-supervised classification on the graph learned from the original data matrix, which doesn't have explicit cluster structure, thus they might not achieve the optimal performance.

Classification General Classification +1

A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception

1 code implementation7 Aug 2020 Chenglizhao Chen, Jia Song, Chong Peng, Guodong Wang, Yuming Fang

Consequently, we can achieve a significant performance improvement by using this new training set to start a new round of network training.

object-detection Salient Object Detection +1

Full Reference Screen Content Image Quality Assessment by Fusing Multi-level Structure Similarity

1 code implementation7 Aug 2020 Chenglizhao Chen, Hongmeng Zhao, Huan Yang, Chong Peng, Teng Yu

The screen content images (SCIs) usually comprise various content types with sharp edges, in which the artifacts or distortions can be well sensed by the vanilla structure similarity measurement in a full reference manner.

Image Quality Assessment

Depth Quality Aware Salient Object Detection

1 code implementation7 Aug 2020 Chenglizhao Chen, Jipeng Wei, Chong Peng, Hong Qin

The existing fusion based RGB-D salient object detection methods usually adopt the bi-stream structure to strike the fusion trade-off between RGB and depth (D).

object-detection RGB-D Salient Object Detection +2

Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection

1 code implementation7 Aug 2020 Chenglizhao Chen, Guotao Wang, Chong Peng, Dingwen Zhang, Yuming Fang, Hong Qin

In this way, even though the overall video saliency quality is heavily dependent on its spatial branch, however, the performance of the temporal branch still matter.

object-detection Salient Object Detection +2

Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering

no code implementations19 May 2020 Chong Peng, Zhilu Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng

In particular, projection matrices are sought under the guidance of building new data representations, such that the spatial information is retained and projections are enhanced by the goal of clustering, which helps construct optimal projection directions.

Structure Learning with Similarity Preserving

no code implementations3 Dec 2019 Zhao Kang, Xiao Lu, Yiwei Lu, Chong Peng, Zenglin Xu

Leveraging on the underlying low-dimensional structure of data, low-rank and sparse modeling approaches have achieved great success in a wide range of applications.

Nonnegative Matrix Factorization with Local Similarity Learning

no code implementations9 Jul 2019 Chong Peng, Zhao Kang, Chenglizhao Chen, Qiang Cheng

Existing nonnegative matrix factorization methods focus on learning global structure of the data to construct basis and coefficient matrices, which ignores the local structure that commonly exists among data.

Discriminative Ridge Machine: A Classifier for High-Dimensional Data or Imbalanced Data

no code implementations16 Apr 2019 Chong Peng, Qiang Cheng

As a special case we focus on a quadratic model that admits a closed-form analytical solution.

regression

Unified Spectral Clustering with Optimal Graph

1 code implementation12 Nov 2017 Zhao Kang, Chong Peng, Qiang Cheng, Zenglin Xu

Second, the discrete solution may deviate from the spectral solution since k-means method is well-known as sensitive to the initialization of cluster centers.

graph construction

Twin Learning for Similarity and Clustering: A Unified Kernel Approach

no code implementations1 May 2017 Zhao Kang, Chong Peng, Qiang Cheng

Thus the learned similarity matrix is often not suitable, let alone optimal, for the subsequent clustering.

Top-N Recommendation on Graphs

1 code implementation27 Sep 2016 Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng

To alleviate this problem, this paper proposes a simple recommendation algorithm that fully exploits the similarity information among users and items and intrinsic structural information of the user-item matrix.

Collaborative Filtering Recommendation Systems

A Fast Factorization-based Approach to Robust PCA

no code implementations27 Sep 2016 Chong Peng, Zhao Kang, Qiang Chen

Our method can be used as a light-weight, scalable tool for RPCA in the absence of the precise value of the true rank.

Top-N Recommender System via Matrix Completion

no code implementations19 Jan 2016 Zhao Kang, Chong Peng, Qiang Cheng

Top-N recommender systems have been investigated widely both in industry and academia.

Matrix Completion Recommendation Systems

Robust PCA via Nonconvex Rank Approximation

1 code implementation17 Nov 2015 Zhao Kang, Chong Peng, Qiang Cheng

This approximation to the matrix rank is tighter than the nuclear norm.

Robust Subspace Clustering via Tighter Rank Approximation

1 code implementation30 Oct 2015 Zhao Kang, Chong Peng, Qiang Cheng

For this nonconvex minimization problem, we develop an effective optimization procedure based on a type of augmented Lagrange multipliers (ALM) method.

Face Clustering Motion Segmentation

Robust Subspace Clustering via Smoothed Rank Approximation

1 code implementation18 Aug 2015 Zhao Kang, Chong Peng, Qiang Cheng

However, for many real-world applications, nuclear norm approximation to the rank function can only produce a result far from the optimum.

Face Clustering Motion Segmentation

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