b'Yuanyuan Liu'

research

∙ 08/30/2023

Physics-Informed DeepMRI: Bridging the Gap from Heat Diffusion to k-Space Interpolation

In the field of parallel imaging (PI), alongside image-domain regulariza...

0 Zhuo-Xu Cui, et al. ∙

research

∙ 08/21/2023

Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer

Deep neural networks are vulnerable to adversarial examples crafted by a...

0 Zhijin Ge, et al. ∙

research

∙ 08/09/2023

A Hierarchical Destroy and Repair Approach for Solving Very Large-Scale Travelling Salesman Problem

For prohibitively large-scale Travelling Salesman Problems (TSPs), exist...

0 Zhang-Hua Fu, et al. ∙

research

∙ 06/29/2023

A Fast Fourier Convolutional Deep Neural Network For Accurate and Explainable Discrimination Of Wheat Yellow Rust And Nitrogen Deficiency From Sentinel-2 Time-Series Data

Accurate and timely detection of plant stress is essential for yield pro...

0 Yue Shi, et al. ∙

research

∙ 06/08/2023

Boosting Adversarial Transferability by Achieving Flat Local Maxima

Transfer-based attack adopts the adversarial examples generated on the s...

0 Zhijin Ge, et al. ∙

research

∙ 05/04/2023

Noise-Resistant Multimodal Transformer for Emotion Recognition

Multimodal emotion recognition identifies human emotions from various da...

0 Yuanyuan Liu, et al. ∙

research

∙ 05/04/2023

Meta-Learning Enabled Score-Based Generative Model for 1.5T-Like Image Reconstruction from 0.5T MRI

Magnetic resonance imaging (MRI) is known to have reduced signal-to-nois...

0 Zhuo-Xu Cui, et al. ∙

research

∙ 11/24/2022

Pose-disentangled Contrastive Learning for Self-supervised Facial Representation

Self-supervised facial representation has recently attracted increasing ...

0 Yuanyuan Liu, et al. ∙

research

∙ 10/12/2022

Explore Contextual Information for 3D Scene Graph Generation

3D scene graph generation (SGG) has been of high interest in computer vi...

0 Yuanyuan Liu, et al. ∙

research

∙ 09/02/2022

PCDNF: Revisiting Learning-based Point Cloud Denoising via Joint Normal Filtering

Recovering high quality surfaces from noisy point clouds, known as point...

5 Zheng Liu, et al. ∙

research

∙ 08/11/2022

K-UNN: k-Space Interpolation With Untrained Neural Network

Recently, untrained neural networks (UNNs) have shown satisfactory perfo...

24 Zhuo-Xu Cui, et al. ∙

research

∙ 08/01/2022

MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild

Dynamic facial expression recognition (FER) databases provide important ...

0 Yuanyuan Liu, et al. ∙

research

∙ 03/29/2022

On Convergence of General Truncation-Augmentation Schemes for Approximating Stationary Distributions of Markov Chains

In the analysis of Markov chains and processes, it is sometimes convenie...

0 Alex Infanger, et al. ∙

research

∙ 01/17/2022

Dual Perceptual Loss for Single Image Super-Resolution Using ESRGAN

The proposal of perceptual loss solves the problem that per-pixel differ...

2 Jie Song, et al. ∙

research

∙ 12/18/2021

Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRI

Recently, model-driven deep learning unrolls a certain iterative algorit...

13 Zhuo-Xu Cui, et al. ∙

research

∙ 12/01/2021

Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning

Purpose: To propose a novel deep learning-based method called RG-Net (re...

6 Yanjie Zhu, et al. ∙

research

∙ 09/17/2021

Expression Snippet Transformer for Robust Video-based Facial Expression Recognition

The recent success of Transformer has provided a new direction to variou...

35 Yuanyuan Liu, et al. ∙

research

∙ 08/16/2021

Language-Independent Approach for Automatic Computation of Vowel Articulation Features in Dysarthric Speech Assessment

Imprecise vowel articulation can be observed in people with Parkinson's ...

0 Yuanyuan Liu, et al. ∙

research

∙ 06/23/2021

Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning

Federated Learning (FL) has become an active and promising distributed m...

0 Hua Huang, et al. ∙

research

∙ 06/22/2021

Learned Interpretable Residual Extragradient ISTA for Sparse Coding

Recently, the study on learned iterative shrinkage thresholding algorith...

0 Lin Kong, et al. ∙

research

∙ 03/22/2021

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

Video super-resolution (VSR) aims at restoring a video in low-resolution...

0 Hongying Liu, et al. ∙

research

∙ 11/26/2020

Outlier-robust Kalman Filter in the Presence of Correlated Measurements

We consider the robust filtering problem for a state-space model with ou...

0 Hongwei Wang, et al. ∙

research

∙ 10/31/2020

Differentially Private ADMM Algorithms for Machine Learning

In this paper, we study efficient differentially private alternating dir...

18 Tao Xu, et al. ∙

research

∙ 10/21/2020

Boosting Gradient for White-Box Adversarial Attacks

Deep neural networks (DNNs) are playing key roles in various artificial ...

0 Hongying Liu, et al. ∙

research

∙ 08/24/2020

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

Spherical videos, also known as 360 (panorama) videos, can be viewed wit...

0 Hongying Liu, et al. ∙

research

∙ 07/25/2020

Video Super Resolution Based on Deep Learning: A comprehensive survey

In recent years, deep learning has made great progress in the fields of ...

0 Hongying Liu, et al. ∙

research

∙ 12/20/2019

An Unsupervised Deep Learning Method for Parallel Cardiac MRI via Time-Interleaved Sampling

Deep learning has achieved good success in cardiac magnetic resonance im...

0 Yanjie Zhu, et al. ∙

research

∙ 12/02/2019

Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization

Large-scale non-convex sparsity-constrained problems have recently gaine...

0 Fanhua Shang, et al. ∙

research

∙ 05/24/2019

Pose-adaptive Hierarchical Attention Network for Facial Expression Recognition

Multi-view facial expression recognition (FER) is a challenging task bec...

0 Yuanyuan Liu, et al. ∙

research

∙ 12/04/2018

Parallel-tempered Stochastic Gradient Hamiltonian Monte Carlo for Approximate Multimodal Posterior Sampling

We propose a new sampler that integrates the protocol of parallel temper...

0 Rui Luo, et al. ∙

research

∙ 11/08/2018

Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series

Volatility is a quantity of measurement for the price movements of stock...

0 Qiang Zhang, et al. ∙

research

∙ 10/11/2018

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications

The heavy-tailed distributions of corrupted outliers and singular values...

0 Fanhua Shang, et al. ∙

research

∙ 02/28/2018

Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization

The Schatten quasi-norm was introduced to bridge the gap between the tra...

0 Fanhua Shang, et al. ∙

research

∙ 02/26/2018

Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization

In this paper, we propose a novel sufficient decrease technique for stoc...

0 Fanhua Shang, et al. ∙

research

∙ 11/30/2017

Thermostat-assisted Continuous-tempered Hamiltonian Monte Carlo for Multimodal Posterior Sampling

In this paper, we propose a new sampling method named as the thermostat-...

0 Rui Luo, et al. ∙

research

∙ 07/11/2017

Accelerated Variance Reduced Stochastic ADMM

Recently, many variance reduced stochastic alternating direction method ...

0 Yuanyuan Liu, et al. ∙

research

∙ 03/23/2017

Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning

Recently, research on accelerated stochastic gradient descent methods (e...

0 Fanhua Shang, et al. ∙

research

∙ 03/20/2017

Guaranteed Sufficient Decrease for Variance Reduced Stochastic Gradient Descent

In this paper, we propose a novel sufficient decrease technique for vari...

0 Fanhua Shang, et al. ∙

research

∙ 06/04/2016

Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization

The Schatten-p quasi-norm (0<p<1) is usually used to replace the standar...

0 Fanhua Shang, et al. ∙

research

∙ 06/02/2016

Unified Scalable Equivalent Formulations for Schatten Quasi-Norms

The Schatten quasi-norm can be used to bridge the gap between the nuclea...

0 Fanhua Shang, et al. ∙

research

∙ 09/03/2014

Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations

Recovering low-rank and sparse matrices from incomplete or corrupted obs...

0 Fanhua Shang, et al. ∙

Yuanyuan Liu

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