Search Results for author: Xiaofeng Zhu

Found 27 papers, 8 papers with code

Federated Deep Multi-View Clustering with Global Self-Supervision

no code implementations24 Sep 2023 Xinyue Chen, Jie Xu, Yazhou Ren, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He

Second, the storage and usage of data from multiple clients in a distributed environment can lead to incompleteness of multi-view data.

FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning

no code implementations19 Sep 2023 Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Taotao Cai, Xiaofeng Zhu, Qing Li

These issues compromise both the accuracy and the computational efficiency of models in both Machine Learning and Unlearning.

Federated Learning Privacy Preserving +1

Zero-shot information extraction from radiological reports using ChatGPT

no code implementations4 Sep 2023 Danqing Hu, Bing Liu, Xiaofeng Zhu, Xudong Lu, Nan Wu

Information extraction is the strategy to transform the sequence of characters into structured data, which can be employed for secondary analysis.

Language Modelling Large Language Model +3

Unsupervised Multiplex Graph Learning with Complementary and Consistent Information

1 code implementation3 Aug 2023 Liang Peng, Xin Wang, Xiaofeng Zhu

Unsupervised multiplex graph learning (UMGL) has been shown to achieve significant effectiveness for different downstream tasks by exploring both complementary information and consistent information among multiple graphs.

Graph Learning Representation Learning

A Universal Unbiased Method for Classification from Aggregate Observations

no code implementations20 Jun 2023 Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen

This motivates the study on classification from aggregate observations (CFAO), where the supervision is provided to groups of instances, instead of individual instances.

Classification Multiple Instance Learning

Using Caterpillar to Nibble Small-Scale Images

no code implementations28 May 2023 Jin Sun, Xiaoshuang Shi, Zhiyuan Weng, Kaidi Xu, Heng Tao Shen, Xiaofeng Zhu

Recently, MLP-based models have become popular and attained significant performance on medium-scale datasets (e. g., ImageNet-1k).

Inductive Bias

An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization

no code implementations26 May 2023 Fei Kong, Jinhao Duan, RuiPeng Ma, HengTao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu

Therefore, we also explore the robustness of diffusion models to MIA in the text-to-speech (TTS) task, which is an audio generation task.

Audio Generation Inference Attack +1

Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy

no code implementations10 May 2023 Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Xiaofeng Zhu, Qing Li

Machine unlearning (MU) is gaining increasing attention due to the need to remove or modify predictions made by machine learning (ML) models.

Fairness Recommendation Systems

Explicit and Implicit Semantic Ranking Framework

no code implementations11 Apr 2023 Xiaofeng Zhu, Thomas Lin, Vishal Anand, Matthew Calderwood, Eric Clausen-Brown, Gord Lueck, Wen-wai Yim, Cheng Wu

The core challenge in numerous real-world applications is to match an inquiry to the best document from a mutable and finite set of candidates.

Learning-To-Rank Text Summarization

Self-Paced Neutral Expression-Disentangled Learning for Facial Expression Recognition

no code implementations21 Mar 2023 Zhenqian Wu, Xiaoyuan Li, Yazhou Ren, Xiaorong Pu, Xiaofeng Zhu, Lifang He

In order to better learn these neutral expression-disentangled features (NDFs) and to alleviate the non-convex optimization problem, a self-paced learning (SPL) strategy based on NDFs is proposed in the training stage.

Facial Expression Recognition

GATE: Graph CCA for Temporal SElf-supervised Learning for Label-efficient fMRI Analysis

1 code implementation17 Mar 2022 Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, Xiaoxiao Li

To improve fMRI representation learning and classification under a label-efficient setting, we propose a novel and theory-driven self-supervised learning (SSL) framework on GCNs, namely Graph CCA for Temporal self-supervised learning on fMRI analysis GATE.

Classification Representation Learning +1

Self-paced Principal Component Analysis

no code implementations25 Jun 2021 Zhao Kang, Hongfei Liu, Jiangxin Li, Xiaofeng Zhu, Ling Tian

Notably, the complexity of each sample is calculated at the beginning of each iteration in order to integrate samples from simple to more complex into training.

Dimensionality Reduction

Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering

no code implementations ICCV 2021 Jie Xu, Yazhou Ren, Huayi Tang, Xiaorong Pu, Xiaofeng Zhu, Ming Zeng, Lifang He

The prior of view-common variable obeys approximately discrete Gumbel Softmax distribution, which is introduced to extract the common cluster factor of multiple views.


Multi-level Feature Learning for Contrastive Multi-view Clustering

1 code implementation CVPR 2022 Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He

Our method learns different levels of features from the raw features, including low-level features, high-level features, and semantic labels/features in a fusion-free manner, so that it can effectively achieve the reconstruction objective and the consistency objectives in different feature spaces.

Clustering Contrastive Learning

Self-paced Resistance Learning against Overfitting on Noisy Labels

1 code implementation7 May 2021 Xiaoshuang Shi, Zhenhua Guo, Kang Li, Yun Liang, Xiaofeng Zhu

They might significantly deteriorate the performance of convolutional neural networks (CNNs), because CNNs are easily overfitted on corrupted labels.


Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view

no code implementations16 Feb 2021 Zhao Kang, Zhiping Lin, Xiaofeng Zhu, Wenbo Xu

Extensive experiments demonstrate the efficiency and effectiveness of our approach with respect to many state-of-the-art clustering methods.

Clustering Graph Learning

Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan

no code implementations7 May 2020 Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen

To our knowledge, this study is the first work to predict the disease progression and the conversion time, which could help clinicians to deal with the potential severe cases in time or even save the patients' lives.

Classification Computed Tomography (CT) +2

Neural Network Retraining for Model Serving

no code implementations29 Apr 2020 Diego Klabjan, Xiaofeng Zhu

We address two challenges of life-long retraining: catastrophic forgetting and efficient retraining.

Multi-Armed Bandits

Listwise Learning to Rank by Exploring Unique Ratings

1 code implementation7 Jan 2020 Xiaofeng Zhu, Diego Klabjan

We encode all of the documents already selected by an RNN model.


Frosting Weights for Better Continual Training

1 code implementation7 Jan 2020 Xiaofeng Zhu, Feng Liu, Goce Trajcevski, Dingding Wang

Training a neural network model can be a lifelong learning process and is a computationally intensive one.


High dynamic range image forensics using cnn

no code implementations28 Feb 2019 Yongqing Huo, Xiaofeng Zhu

High dynamic range (HDR) imaging has recently drawn much attention in multimedia community.

Image Forensics inverse tone mapping +3

Identification of multi-scale hierarchical brain functional networks using deep matrix factorization

no code implementations14 Sep 2018 Hongming Li, Xiaofeng Zhu, Yong Fan

We present a deep semi-nonnegative matrix factorization method for identifying subject-specific functional networks (FNs) at multiple spatial scales with a hierarchical organization from resting state fMRI data.

Semantic Document Distance Measures and Unsupervised Document Revision Detection

1 code implementation IJCNLP 2017 Xiaofeng Zhu, Diego Klabjan, Patrick Bless

In this paper, we model the document revision detection problem as a minimum cost branching problem that relies on computing document distances.

Dynamic Time Warping

Unsupervised Terminological Ontology Learning based on Hierarchical Topic Modeling

1 code implementation29 Aug 2017 Xiaofeng Zhu, Diego Klabjan, Patrick Bless

In this paper, we present hierarchical relationbased latent Dirichlet allocation (hrLDA), a data-driven hierarchical topic model for extracting terminological ontologies from a large number of heterogeneous documents.

Topic Models

Matrix-Similarity Based Loss Function and Feature Selection for Alzheimer's Disease Diagnosis

no code implementations CVPR 2014 Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen

We conducted experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and showed that the newly devised loss function was effective to enhance the performances of both clinical score prediction and disease status identification, outperforming the state-of-the-art methods.

feature selection

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