Search Results for author: Yang Xiang

Found 67 papers, 16 papers with code

Energy stable neural network for gradient flow equations

no code implementations17 Sep 2023 Ganghua Fan, Tianyu Jin, Yuan Lan, Yang Xiang, Luchan Zhang

In this paper, we propose an energy stable network (EStable-Net) for solving gradient flow equations.

Client-side Gradient Inversion Against Federated Learning from Poisoning

1 code implementation14 Sep 2023 Jiaheng Wei, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shirui Pan, Kok-Leong Ong, Jun Zhang, Yang Xiang

For the first time, we show the feasibility of a client-side adversary with limited knowledge being able to recover the training samples from the aggregated global model.

Federated Learning

SHAPE: A Sample-adaptive Hierarchical Prediction Network for Medication Recommendation

no code implementations9 Sep 2023 Sicen Liu, Xiaolong Wang, Jingcheng Du, Yongshuai Hou, Xianbing Zhao, Hui Xu, Hui Wang, Yang Xiang, Buzhou Tang

Effectively medication recommendation with complex multimorbidity conditions is a critical task in healthcare.

Large Transformers are Better EEG Learners

no code implementations20 Aug 2023 Bingxin Wang, Xiaowen Fu, Yuan Lan, Luchan Zhang, Yang Xiang

Since the magnitude of available labeled electroencephalogram (EEG) data is much lower than that of text and image data, it is difficult for transformer models pre-trained from EEG to be developed as large as GPT-4 100T to fully unleash the potential of this architecture.

EEG Eeg Decoding +1

Model Provenance via Model DNA

no code implementations4 Aug 2023 Xin Mu, Yu Wang, Yehong Zhang, JiaQi Zhang, Hui Wang, Yang Xiang, Yue Yu

Understanding the life cycle of the machine learning (ML) model is an intriguing area of research (e. g., understanding where the model comes from, how it is trained, and how it is used).

Representation Learning

Stability Analysis Framework for Particle-based Distance GANs with Wasserstein Gradient Flow

no code implementations4 Jul 2023 Chuqi Chen, Yue Wu, Yang Xiang

In this paper, we analyze the stability of the training process of these GANs from the perspective of probability density dynamics.

Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives

no code implementations15 May 2023 Yahong Yang, Haizhao Yang, Yang Xiang

This paper addresses the problem of nearly optimal Vapnik--Chervonenkis dimension (VC-dimension) and pseudo-dimension estimations of the derivative functions of deep neural networks (DNNs).

Operator learning Physics-informed machine learning

Score-based Transport Modeling for Mean-Field Fokker-Planck Equations

no code implementations21 Apr 2023 Jianfeng Lu, Yue Wu, Yang Xiang

We use the score-based transport modeling method to solve the mean-field Fokker-Planck equations, which we call MSBTM.

Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection

no code implementations30 Mar 2023 Chuer Yu, Xuhong Zhang, Yuxuan Duan, Senbo Yan, Zonghui Wang, Yang Xiang, Shouling Ji, Wenzhi Chen

We then visualize the identity loss between the test and the reference image from the image differences of the aligned pairs, and design a custom metric to quantify the identity loss.

DeepFake Detection Face Swapping

Elastic Interaction Energy-Based Generative Model: Approximation in Feature Space

no code implementations19 Mar 2023 Chuqi Chen, Yue Wu, Yang Xiang

We adopt the GAN framework and replace the discriminator with a feature transformation network to map the data into a latent space.

DOSnet as a Non-Black-Box PDE Solver: When Deep Learning Meets Operator Splitting

no code implementations11 Dec 2022 Yuan Lan, Zhen Li, Jie Sun, Yang Xiang

Deep neural networks (DNNs) recently emerged as a promising tool for analyzing and solving complex differential equations arising in science and engineering applications.

An Efficient Split Fine-tuning Framework for Edge and Cloud Collaborative Learning

no code implementations30 Nov 2022 Shaohuai Shi, Qing Yang, Yang Xiang, Shuhan Qi, Xuan Wang

To enable the pre-trained models to be fine-tuned with local data on edge devices without sharing data with the cloud, we design an efficient split fine-tuning (SFT) framework for edge and cloud collaborative learning.

Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation

no code implementations27 Oct 2022 Xutao Guo, Yanwu Yang, Chenfei Ye, Shang Lu, Yang Xiang, Ting Ma

Based on the Denoising Diffusion Probabilistic Model (DDPM), medical image segmentation can be described as a conditional image generation task, which allows to compute pixel-wise uncertainty maps of the segmentation and allows an implicit ensemble of segmentations to boost the segmentation performance.

Conditional Image Generation Denoising +3

Multi-modal Dynamic Graph Network: Coupling Structural and Functional Connectome for Disease Diagnosis and Classification

no code implementations25 Oct 2022 Yanwu Yang, Xutao Guo, Zhikai Chang, Chenfei Ye, Yang Xiang, Ting Ma

Graph neural networks have been proven to be of great importance in modeling brain connectome networks and relating disease-specific patterns.

Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles

1 code implementation21 Oct 2022 Yuxuan Han, Jialin Zeng, Yang Wang, Yang Xiang, Jiheng Zhang

We study the stochastic contextual bandit with knapsacks (CBwK) problem, where each action, taken upon a context, not only leads to a random reward but also costs a random resource consumption in a vector form.

Multi-Armed Bandits regression

GOLLIC: Learning Global Context beyond Patches for Lossless High-Resolution Image Compression

no code implementations7 Oct 2022 Yuan Lan, Liang Qin, Zhaoyi Sun, Yang Xiang, Jie Sun

Besides the latent variable unique to each patch, we introduce shared latent variables between patches to construct the global context.

Clustering Data Compression +1

The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices

1 code implementation23 Sep 2022 Wanlun Ma, Derui Wang, Ruoxi Sun, Minhui Xue, Sheng Wen, Yang Xiang

However, recent advanced backdoor attacks show that this assumption is no longer valid in dynamic backdoors where the triggers vary from input to input, thereby defeating the existing defenses.

Estimating Brain Age with Global and Local Dependencies

no code implementations19 Sep 2022 Yanwu Yang, Xutao Guo, Zhikai Chang, Chenfei Ye, Yang Xiang, Haiyan Lv, Ting Ma

The brain age has been proven to be a phenotype of relevance to cognitive performance and brain disease.

Feature Engineering Inductive Bias

Approximation of Functionals by Neural Network without Curse of Dimensionality

no code implementations28 May 2022 Yahong Yang, Yang Xiang

In this paper, we establish a neural network to approximate functionals, which are maps from infinite dimensional spaces to finite dimensional spaces.

Nebula-I: A General Framework for Collaboratively Training Deep Learning Models on Low-Bandwidth Cloud Clusters

1 code implementation19 May 2022 Yang Xiang, Zhihua Wu, Weibao Gong, Siyu Ding, Xianjie Mo, Yuang Liu, Shuohuan Wang, Peng Liu, Yongshuai Hou, Long Li, Bin Wang, Shaohuai Shi, Yaqian Han, Yue Yu, Ge Li, Yu Sun, Yanjun Ma, dianhai yu

We took natural language processing (NLP) as an example to show how Nebula-I works in different training phases that include: a) pre-training a multilingual language model using two remote clusters; and b) fine-tuning a machine translation model using knowledge distilled from pre-trained models, which run through the most popular paradigm of recent deep learning.

Cross-Lingual Natural Language Inference Distributed Computing +2

A deep representation learning speech enhancement method using $β$-VAE

no code implementations11 May 2022 Yang Xiang, Jesper Lisby Højvang, Morten Højfeldt Rasmussen, Mads Græsbøll Christensen

In previous work, we proposed a variational autoencoder-based (VAE) Bayesian permutation training speech enhancement (SE) method (PVAE) which indicated that the SE performance of the traditional deep neural network-based (DNN) method could be improved by deep representation learning (DRL).

Disentanglement Speech Enhancement

CATNet: Cross-event Attention-based Time-aware Network for Medical Event Prediction

no code implementations29 Apr 2022 Sicen Liu, Xiaolong Wang, Yang Xiang, Hui Xu, Hui Wang, Buzhou Tang

It is a time-aware, event-aware and task-adaptive method with the following advantages: 1) modeling heterogeneous information and temporal information in a unified way and considering temporal irregular characteristics locally and globally respectively, 2) taking full advantage of correlations among different types of events via cross-event attention.

Time Series Analysis

Multimodal data matters: language model pre-training over structured and unstructured electronic health records

1 code implementation25 Jan 2022 Sicen Liu, Xiaolong Wang, Yongshuai Hou, Ge Li, Hui Wang, Hui Xu, Yang Xiang, Buzhou Tang

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain.

Decision Making Language Modelling +1

Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives

no code implementations9 Nov 2021 Ziyi Liu, JiaQi Zhang, Yongshuai Hou, Xinran Zhang, Ge Li, Yang Xiang

Background: Electronic Health Records (EHRs) contain rich information of patients' health history, which usually include both structured and unstructured data.

BIG-bench Machine Learning

Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data

1 code implementation3 Oct 2021 Laila Rasmy, Jie Zhu, Zhiheng Li, Xin Hao, Hong Thoai Tran, Yujia Zhou, Firat Tiryaki, Yang Xiang, Hua Xu, Degui Zhi

As a result, deep learning models developed for sequence modeling, like recurrent neural networks (RNNs) are common architecture for EHR-based clinical events predictive models.

Bayesian Optimization

GlyphCRM: Bidirectional Encoder Representation for Chinese Character with its Glyph

no code implementations1 Jul 2021 Yunxin Li, Yu Zhao, Baotian Hu, Qingcai Chen, Yang Xiang, Xiaolong Wang, Yuxin Ding, Lin Ma

Previous works indicate that the glyph of Chinese characters contains rich semantic information and has the potential to enhance the representation of Chinese characters.

Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks

no code implementations5 Jun 2021 Yue Wu, Yuan Lan, Luchan Zhang, Yang Xiang

Pruning is a model compression method that removes redundant parameters in deep neural networks (DNNs) while maintaining accuracy.

Model Compression

Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey

no code implementations13 May 2021 XiaoYu Zhang, Chao Chen, Yi Xie, Xiaofeng Chen, Jun Zhang, Yang Xiang

This survey presents the most recent findings of privacy attacks and defenses appeared in cloud-based neural network services.

Cloud Computing

Internal Wasserstein Distance for Adversarial Attack and Defense

no code implementations13 Mar 2021 Qicheng Wang, Shuhai Zhang, JieZhang Cao, Jincheng Li, Mingkui Tan, Yang Xiang

Existing attack methods often construct adversarial examples relying on some metrics like the $\ell_p$ distance to perturb samples.

Adversarial Attack Adversarial Defense +2

Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey

2 code implementations16 Feb 2021 Yuantian Miao, Chao Chen, Lei Pan, Qing-Long Han, Jun Zhang, Yang Xiang

Stealing attack against controlled information, along with the increasing number of information leakage incidents, has become an emerging cyber security threat in recent years.

BIG-bench Machine Learning

Continuum Model and Numerical Method for Dislocation Structure and Energy of Grain Boundaries

no code implementations7 Jan 2021 Xiaoxue Qin, Yejun Gu, Luchan Zhang, Yang Xiang

We present a continuum model to determine the dislocation structure and energy of low angle grain boundaries in three dimensions.

Materials Science

Continuum model for dislocation structures of semicoherent interfaces

no code implementations6 Dec 2020 Luchan Zhang, Xiaoxue Qin, Yang Xiang

In our continuum model, the dislocation structure of a semicoherent interface is obtained by minimizing the energy of the equilibrium dislocation network with respect to all the possible Burgers vectors, subject to the constraint of the Frank-Bilby equation.

Materials Science

DeFuzz: Deep Learning Guided Directed Fuzzing

no code implementations23 Oct 2020 Xiaogang Zhu, Shigang Liu, Xian Li, Sheng Wen, Jun Zhang, Camtepe Seyit, Yang Xiang

Fuzzing is one of the most effective technique to identify potential software vulnerabilities.

Vulnerability Detection

Analysis of Trending Topics and Text-based Channels of Information Delivery in Cybersecurity

no code implementations26 Jun 2020 Tingmin Wu, Wanlun Ma, Sheng Wen, Xin Xia, Cecile Paris, Surya Nepal, Yang Xiang

We further compare the identified 16 security categories across different sources based on their popularity and impact.

Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction

1 code implementation22 May 2020 Laila Rasmy, Yang Xiang, Ziqian Xie, Cui Tao, Degui Zhi

Deep learning (DL) based predictive models from electronic health records (EHR) deliver impressive performance in many clinical tasks.

Disease Prediction

A Study of Data Pre-processing Techniques for Imbalanced Biomedical Data Classification

no code implementations4 Nov 2019 Shigang Liu, Jun Zhang, Yang Xiang, Wanlei Zhou, Dongxi Xiang

However, previous studies usually focused on different classifiers, and overlook the class imbalance problem in real-world biomedical datasets.

Drug Discovery feature selection +1

Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models

no code implementations14 Oct 2019 Derui, Wang, Chaoran Li, Sheng Wen, Surya Nepal, Yang Xiang

First, such attacks must acquire the outputs from the models by multiple times before actually launching attacks, which is difficult for the MitM adversary in practice.

BIG-bench Machine Learning

Hybrid Neural Tagging Model for Open Relation Extraction

no code implementations26 Jul 2019 Shengbin Jia, Yang Xiang

Furthermore, we propose a hybrid neural network model (HNN4ORT) for open relation tagging.

Feature Engineering Relation Extraction

Naive Bayes and BiLSTM Ensemble for Discriminating between Mainland and Taiwan Variation of Mandarin Chinese

no code implementations WS 2019 Li Yang, Yang Xiang

Automatic dialect identification is a more challengingctask than language identification, as it requires the ability to discriminate between varieties of one language.

Dialect Identification Word Embeddings

A Truthful FPTAS Mechanism for Emergency Demand Response in Colocation Data Centers

1 code implementation10 Jan 2019 Jian-hai Chen, Deshi Ye, Shouling Ji, Qinming He, Yang Xiang, Zhenguang Liu

Next, we prove that our mechanism is an FPTAS, i. e., it can be approximated within $1 + \epsilon$ for any given $\epsilon > 0$, while the running time of our mechanism is polynomial in $n$ and $1/\epsilon$, where $n$ is the number of tenants in the datacenter.

Computer Science and Game Theory

ML-Net: multi-label classification of biomedical texts with deep neural networks

4 code implementations13 Nov 2018 Jingcheng Du, Qingyu Chen, Yifan Peng, Yang Xiang, Cui Tao, Zhiyong Lu

Due to this nature, the multi-label text classification task is often considered to be more challenging compared to the binary or multi-class text classification problems.

Benchmarking Feature Engineering +4

An objective-adaptive refinement criterion based on modified ridge extraction method for finite-time Lyapunov exponent (FTLE) calculation

no code implementations13 Nov 2018 Haotian Hang, Bin Yu, Yang Xiang, Bin Zhang, Hong Liu

High-accuracy and high-efficiency finite-time Lyapunov exponent (FTLE) calculation method has long been a research hot point, and adaptive refinement method is a kind of method in this field.

Fluid Dynamics

Chinese User Service Intention Classification Based on Hybrid Neural Network

no code implementations25 Sep 2018 Shengbin Jia, Yang Xiang

It is difficult for the intelligent system to understand the semantics of user demand which leads to poor recognition effect, because of the noise in user requirement descriptions.

Classification General Classification +2

Triple Trustworthiness Measurement for Knowledge Graph

1 code implementation25 Sep 2018 Shengbin Jia, Yang Xiang, Xiaojun Chen

The Knowledge graph (KG) uses the triples to describe the facts in the real world.

Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection

no code implementations10 Aug 2018 Xiao Chen, Chaoran Li, Derui Wang, Sheng Wen, Jun Zhang, Surya Nepal, Yang Xiang, Kui Ren

In contrast to existing works, the adversarial examples crafted by our method can also deceive recent machine learning based detectors that rely on semantic features such as control-flow-graph.

Cryptography and Security

Automated Big Traffic Analytics for Cyber Security

no code implementations24 Apr 2018 Yuantian Miao, Zichan Ruan, Lei Pan, Yu Wang, Jun Zhang, Yang Xiang

Network traffic analytics technology is a cornerstone for cyber security systems.

Cryptography and Security

Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training

no code implementations14 Mar 2018 Derek Wang, Chaoran Li, Sheng Wen, Surya Nepal, Yang Xiang

For example, proactive defending methods are invalid against grey-box or white-box attacks, while reactive defending methods are challenged by low-distortion adversarial examples or transferring adversarial examples.

Adversarial Attack

Wikipedia Vandal Early Detection: from User Behavior to User Embedding

1 code implementation3 Jun 2017 Shuhan Yuan, Panpan Zheng, Xintao Wu, Yang Xiang

In particular, we develop a multi-source long-short term memory network (M-LSTM) to model user behaviors by using a variety of user edit aspects as inputs, including the history of edit reversion information, edit page titles and categories.

Task-specific Word Identification from Short Texts Using a Convolutional Neural Network

no code implementations3 Jun 2017 Shuhan Yuan, Xintao Wu, Yang Xiang

The other case study on fake review detection shows that our approach can identify the fake-review words/phrases.

Incorporating Label Dependency for Answer Quality Tagging in Community Question Answering via CNN-LSTM-CRF

1 code implementation COLING 2016 Yang Xiang, Xiaoqiang Zhou, Qingcai Chen, Zhihui Zheng, Buzhou Tang, Xiaolong Wang, Yang Qin

In community question answering (cQA), the quality of answers are determined by the matching degree between question-answer pairs and the correlation among the answers.

Community Question Answering

Representation Learning Models for Entity Search

no code implementations28 Oct 2016 Shijia E, Yang Xiang, Mohan Zhang

We focus on the problem of learning distributed representations for entity search queries, named entities, and their short descriptions.

Representation Learning

The Dependent Random Measures with Independent Increments in Mixture Models

no code implementations27 Jun 2016 Cheng Luo, Richard Yi Da Xu, Yang Xiang

One of the propositions of the dependent random measures is that the atoms of the posterior distribution are shared amongst groups, and hence groups can borrow information from each other.

Smoothed Hierarchical Dirichlet Process: A Non-Parametric Approach to Constraint Measures

no code implementations16 Apr 2016 Cheng Luo, Yang Xiang, Richard Yi Da Xu

The key novelty of this model is that we place a temporal constraint amongst the nearby discrete measures $\{G_j\}$ in the form of symmetric Kullback-Leibler (KL) Divergence with a fixed bound $B$.

Can Uncertainty Management be Realized in a Finite Totally Ordered Probability Algebra?

no code implementations27 Mar 2013 Yang Xiang, Michael P. Beddoes, David L. Poole

In this paper, the feasibility of using finite totally ordered probability models under Alelinnas's Theory of Probabilistic Logic [Aleliunas, 1988] is investigated.


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