Search Results for author: Min Wu

Found 36 papers, 11 papers with code

Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment

no code implementations21 Sep 2021 Yuecong Xu, Jianfei Yang, Haozhi Cao, Keyu Wu, Min Wu, Rui Zhao, Zhenghua Chen

Multi-Source Domain Adaptation (MSDA) is a more practical domain adaptation scenario in real-world scenarios.

Unsupervised Domain Adaptation

A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based SpO2 Monitoring Using Smartphone Cameras

no code implementations18 Jul 2021 Xin Tian, Chau-Wai Wong, Sushant M. Ranadive, Min Wu

Experimental results show that our proposed blood oxygen estimation method can reach a mean absolute error of 1. 26% when a pulse oximeter is used as a reference, outperforming the traditional RoR method by 25%.

Remote Blood Oxygen Estimation From Videos Using Neural Networks

no code implementations11 Jul 2021 Joshua Mathew, Xin Tian, Min Wu, Chau-Wai Wong

Blood oxygen saturation (SpO$_2$) is an essential indicator of respiratory functionality and is receiving increasing attention during the COVID-19 pandemic.

ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training

no code implementations9 Jul 2021 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li, Cuntai Guan

Second, we design an iterative self-training strategy to align the fine-grained class distributions for the source and target domains via target domain pseudo labels.

Time-Series Representation Learning via Temporal and Contextual Contrasting

1 code implementation26 Jun 2021 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, XiaoLi Li, Cuntai Guan

In this paper, we propose an unsupervised Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC), to learn time-series representation from unlabeled data.

Automatic Sleep Stage Classification Contrastive Learning +8

Feasibility Study on Intra-Grid Location Estimation Using Power ENF Signals

no code implementations3 May 2021 Ravi Garg, Adi Hajj-Ahmad, Min Wu

In this study, we demonstrate that it is possible to pinpoint the location-of-recording to a certain geographical resolution using power signal recordings containing strong ENF traces.

An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG

1 code implementation28 Apr 2021 Emadeldeen Eldele, Zhenghua Chen, Chengyu Liu, Min Wu, Chee-Keong Kwoh, XiaoLi Li, Cuntai Guan

The MRCNN can extract low and high frequency features and the AFR is able to improve the quality of the extracted features by modeling the inter-dependencies between the features.

Automatic Sleep Stage Classification EEG +1

Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray

no code implementations5 Apr 2021 Fakai Wang, Kang Zheng, Yirui Wang, XiaoYun Zhou, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

In this paper, we propose a method to predict BMD from Chest X-ray (CXR), one of the most common, accessible, and low-cost medical image examinations.

Cross-domain Joint Dictionary Learning for ECG Inference from PPG

no code implementations7 Jan 2021 Xin Tian, Qiang Zhu, Yuenan Li, Min Wu

The inverse problem of inferring electrocardiogram (ECG) from photoplethysmogram (PPG) is an emerging research direction that combines the easy measurability of PPG and the rich clinical knowledge of ECG for long-term continuous cardiac monitoring.

Dictionary Learning

Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization

no code implementations CVPR 2021 Fakai Wang, Kang Zheng, Le Lu, Jing Xiao, Min Wu, Shun Miao

This paper proposes a robust and accurate method that effectively exploits the anatomical knowledge of the spine to facilitate vertebra localization and identification.

Rectification

A Lightweight Neural Network for Inferring ECG and Diagnosing Cardiovascular Diseases from PPG

no code implementations9 Dec 2020 Yuenan Li, Xin Tian, Qiang Zhu, Min Wu

We analyze the latent connection between PPG and ECG as well as the CVDs-related features of PPG learned by the neural network, aiming at obtaining clinical insights from data.

Model Compression

Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction

no code implementations20 Jul 2020 Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Ruqiang Yan, Xiao-Li Li

Accurate estimation of remaining useful life (RUL) of industrial equipment can enable advanced maintenance schedules, increase equipment availability and reduce operational costs.

Recent Advances in Network-based Methods for Disease Gene Prediction

1 code implementation19 Jul 2020 Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiao-Li Li

Thirdly, an empirical analysis is conducted to evaluate the performance of the selected methods across seven diseases.

Graph Representation Learning

Transparency Tools for Fairness in AI (Luskin)

no code implementations9 Jul 2020 Mingliang Chen, Aria Shahverdi, Sarah Anderson, Se Yong Park, Justin Zhang, Dana Dachman-Soled, Kristin Lauter, Min Wu

The three tools are: - A new definition of fairness called "controlled fairness" with respect to choices of protected features and filters.

Fairness

Towards Threshold Invariant Fair Classification

no code implementations18 Jun 2020 Mingliang Chen, Min Wu

This paper introduces the notion of threshold invariant fairness, which enforces equitable performances across different groups independent of the decision threshold.

Classification Fairness +1

Multi-View Collaborative Network Embedding

3 code implementations17 May 2020 Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiao-Li Li

Real-world networks often exist with multiple views, where each view describes one type of interaction among a common set of nodes.

Network Embedding

Adaptive Multi-Trace Carving for Robust Frequency Tracking in Forensic Applications

no code implementations14 May 2020 Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu

In the field of information forensics, many emerging problems involve a critical step that estimates and tracks weak frequency components in noisy signals.

Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph

no code implementations24 Apr 2020 Susen Yang, Yong liu, Yonghui Xu, Chunyan Miao, Min Wu, Juyong Zhang

Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG) for recommendation.

Graph Attention

Respiratory Rate Estimation from Face Videos

no code implementations8 Sep 2019 Mingliang Chen, Qiang Zhu, Harrison Zhang, Min Wu, Quanzeng Wang

Commercial cameras are promising contact-free sensors, and remote photoplethysmography (rPPG) have been studied to remotely monitor heart rate from face videos.

Heart Rate Variability Motion Compensation

A Deep Framework for Bone Age Assessment based on Finger Joint Localization

no code implementations7 May 2019 Xiaoman Zhang, Ziyuan Zhao, Cen Chen, Songyou Peng, Min Wu, Zhongyao Cheng, Singee Teo, Le Zhang, Zeng Zeng

In this study, we applied powerful deep neural network and explored a process in the forecast of skeletal bone age with the specifically combine joints images to increase the performance accuracy compared with the whole hand images.

MiniMax Entropy Network: Learning Category-Invariant Features for Domain Adaptation

no code implementations21 Apr 2019 Chaofan Tao, Fengmao Lv, Lixin Duan, Min Wu

Unlike most existing approaches which employ a generator to deal with domain difference, MMEN focuses on learning the categorical information from unlabeled target samples with the help of labeled source samples.

Domain Adaptation

SL$^2$MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

no code implementations20 Oct 2018 Yong Liu, Min Wu, Chenghao Liu, Xiao-Li Li, Jie Zheng

Moreover, we also incorporate biological knowledge about genes from protein-protein interaction (PPI) data and Gene Ontology (GO).

A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees

1 code implementation10 Jul 2018 Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska

In this paper, we study two variants of pointwise robustness, the maximum safe radius problem, which for a given input sample computes the minimum distance to an adversarial example, and the feature robustness problem, which aims to quantify the robustness of individual features to adversarial perturbations.

Adversarial Attack Adversarial Defense +2

Concolic Testing for Deep Neural Networks

2 code implementations30 Apr 2018 Youcheng Sun, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, Daniel Kroening

Concolic testing combines program execution and symbolic analysis to explore the execution paths of a software program.

Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm

2 code implementations16 Apr 2018 Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening, Marta Kwiatkowska

In this paper we focus on the $L_0$ norm and aim to compute, for a trained DNN and an input, the maximal radius of a safe norm ball around the input within which there are no adversarial examples.

Adaptive Cost-sensitive Online Classification

no code implementations6 Apr 2018 Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost.

Anomaly Detection Classification +1

Safety Verification of Deep Neural Networks

2 code implementations21 Oct 2016 Xiaowei Huang, Marta Kwiatkowska, Sen Wang, Min Wu

Our method works directly with the network code and, in contrast to existing methods, can guarantee that adversarial examples, if they exist, are found for the given region and family of manipulations.

Adversarial Attack Adversarial Defense +3

Efficient Estimation of Compressible State-Space Models with Application to Calcium Signal Deconvolution

no code implementations20 Oct 2016 Abbas Kazemipour, Ji Liu, Patrick Kanold, Min Wu, Behtash Babadi

In this paper, we consider linear state-space models with compressible innovations and convergent transition matrices in order to model spatiotemporally sparse transient events.

Sampling Requirements for Stable Autoregressive Estimation

no code implementations4 May 2016 Abbas Kazemipour, Sina Miran, Piya Pal, Behtash Babadi, Min Wu

Assuming that the parameters are compressible, we analyze the performance of the $\ell_1$-regularized least squares as well as a greedy estimator of the parameters and characterize the sampling trade-offs required for stable recovery in the non-asymptotic regime.

Model Selection

Robust Estimation of Self-Exciting Generalized Linear Models with Application to Neuronal Modeling

1 code implementation14 Jul 2015 Abbas Kazemipour, Min Wu, Behtash Babadi

We consider the problem of estimating self-exciting generalized linear models from limited binary observations, where the history of the process serves as the covariate.

Multi-label ensemble based on variable pairwise constraint projection

no code implementations8 Mar 2014 Ping Li, Hong Li, Min Wu

For the boosting-like strategy, we employ both the variable pairwise constraints and the bootstrap steps to diversify the base classifiers.

Classification General Classification +1

Sparse Norm Filtering

no code implementations17 May 2013 Chengxi Ye, DaCheng Tao, Mingli Song, David W. Jacobs, Min Wu

Optimization-based filtering smoothes an image by minimizing a fidelity function and simultaneously preserves edges by exploiting a sparse norm penalty over gradients.

Colorization Deblurring +1

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