Search Results for author: Hongying Liu

Found 16 papers, 4 papers with code

Constrained Optimization Involving Nonconvex $\ell_p$ Norms: Optimality Conditions, Algorithm and Convergence

no code implementations27 Oct 2021 Hao Wang, Yining Gao, Jiashan Wang, Hongying Liu

We also derive the sequential optimality conditions for both problems and study the conditions under which these conditions imply the first-order necessary conditions.

Learned Interpretable Residual Extragradient ISTA for Sparse Coding

no code implementations22 Jun 2021 Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu

Recently, the study on learned iterative shrinkage thresholding algorithm (LISTA) has attracted increasing attentions.

Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling

no code implementations22 Mar 2021 Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu

In this paper, we propose a novel deep neural network with Dual Subnet and Multi-stage Communicated Upsampling (DSMC) for super-resolution of videos with large motion.

Motion Compensation Motion Estimation +1

Differentially Private ADMM Algorithms for Machine Learning

no code implementations31 Oct 2020 Tao Xu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong

For smooth convex loss functions with (non)-smooth regularization, we propose the first differentially private ADMM (DP-ADMM) algorithm with performance guarantee of $(\epsilon,\delta)$-differential privacy ($(\epsilon,\delta)$-DP).

BIG-bench Machine Learning

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution

2 code implementations24 Aug 2020 Hongying Liu, Zhubo Ruan, Chaowei Fang, Peng Zhao, Fanhua Shang, Yuanyuan Liu, Lijun Wang

Spherical videos, also known as \ang{360} (panorama) videos, can be viewed with various virtual reality devices such as computers and head-mounted displays.

Video Super-Resolution

Video Super Resolution Based on Deep Learning: A Comprehensive Survey

no code implementations25 Jul 2020 Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte

To the best of our knowledge, this work is the first systematic review on VSR tasks, and it is expected to make a contribution to the development of recent studies in this area and potentially deepen our understanding to the VSR techniques based on deep learning.

speech-recognition Speech Recognition +1

Efficient High-Dimensional Data Representation Learning via Semi-Stochastic Block Coordinate Descent Methods

no code implementations25 Sep 2019 Bingkun Wei, Yangyang Li, Fanhua Shang, Yuanyuan Liu, Hongying Liu, ShengMei Shen

To address this issue, we propose a novel hard thresholding algorithm, called Semi-stochastic Block Coordinate Descent Hard Thresholding Pursuit (SBCD-HTP).

Face Recognition Representation Learning

Accelerated Variance Reduced Stochastic Extragradient Method for Sparse Machine Learning Problems

no code implementations25 Sep 2019 Fanhua Shang, Lin Kong, Yuanyuan Liu, Hua Huang, Hongying Liu

Moreover, our theoretical analysis shows that AVR-SExtraGD enjoys the best-known convergence rates and oracle complexities of stochastic first-order algorithms such as Katyusha for both strongly convex and non-strongly convex problems.

BIG-bench Machine Learning Face Recognition +1

signADAM: Learning Confidences for Deep Neural Networks

1 code implementation21 Jul 2019 Dong Wang, Yicheng Liu, Wenwo Tang, Fanhua Shang, Hongying Liu, Qigong Sun, Licheng Jiao

In this paper, we propose a new first-order gradient-based algorithm to train deep neural networks.

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning

1 code implementation26 Feb 2018 Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, DaCheng Tao, Licheng Jiao

In this paper, we propose a simple variant of the original SVRG, called variance reduced stochastic gradient descent (VR-SGD).

BIG-bench Machine Learning

Polarimetric Hierarchical Semantic Model and Scattering Mechanism Based PolSAR Image Classification

no code implementations1 Jul 2015 Fang Liu, Junfei Shi, Licheng Jiao, Hongying Liu, Shuyuan Yang, Jie Wu, Hongxia Hao, Jialing Yuan

For polarimetric SAR (PolSAR) image classification, it is a challenge to classify the aggregated terrain types, such as the urban area, into semantic homogenous regions due to sharp bright-dark variations in intensity.

General Classification Image Classification

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