Search Results for author: Li Chen

Found 83 papers, 18 papers with code

Alpha at SemEval-2021 Task 6: Transformer Based Propaganda Classification

no code implementations SEMEVAL 2021 Zhida Feng, Jiji Tang, Jiaxiang Liu, Weichong Yin, Shikun Feng, Yu Sun, Li Chen

This paper describes our system participated in Task 6 of SemEval-2021: the task focuses on multimodal propaganda technique classification and it aims to classify given image and text into 22 classes.

Classification

Decentralized Federated Learning: Balancing Communication and Computing Costs

no code implementations26 Jul 2021 Wei Liu, Li Chen, Wenyi Zhang

Decentralized federated learning (DFL) is a powerful framework of distributed machine learning and decentralized stochastic gradient descent (SGD) is a driving engine for DFL.

Federated Learning

Deep Open Snake Tracker for Vessel Tracing

no code implementations19 Jul 2021 Li Chen, Wenjin Liu, Niranjan Balu, Mahmud Mossa-Basha, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan

Vessel tracing by modeling vascular structures in 3D medical images with centerlines and radii can provide useful information for vascular health.

Task Transformer Network for Joint MRI Reconstruction and Super-Resolution

1 code implementation12 Jun 2021 Chun-Mei Feng, Yunlu Yan, Huazhu Fu, Li Chen, Yong Xu

Then, a task transformer module is designed to embed and synthesize the relevance between the two tasks.

MRI Reconstruction Super-Resolution

$\ell_2$-norm Flow Diffusion in Near-Linear Time

no code implementations30 May 2021 Li Chen, Richard Peng, Di Wang

Diffusion is a fundamental graph procedure and has been a basic building block in a wide range of theoretical and empirical applications such as graph partitioning and semi-supervised learning on graphs.

Graph Clustering Graph Learning +2

Towards a Better Understanding of Linear Models for Recommendation

no code implementations27 May 2021 Ruoming Jin, Dong Li, Jing Gao, Zhi Liu, Li Chen, Yang Zhou

Through the derivation and analysis of the closed-form solutions for two basic regression and matrix factorization approaches, we found these two approaches are indeed inherently related but also diverge in how they "scale-down" the singular values of the original user-item interaction matrix.

Personalized Transformer for Explainable Recommendation

1 code implementation ACL 2021 Lei LI, Yongfeng Zhang, Li Chen

Transformer, which is demonstrated with strong language modeling capability, however, is not personalized and fails to make use of the user and item IDs since the ID tokens are not even in the same semantic space as the words.

Language Modelling Text Generation

Improving Robustness for Pose Estimation via Stable Heatmap Regression

no code implementations8 May 2021 Yumeng Zhang, Li Chen, Yufeng Liu, Xiaoyan Guo, Wen Zheng, Junhai Yong

Deep learning methods have achieved excellent performance in pose estimation, but the lack of robustness causes the keypoints to change drastically between similar images.

Pose Estimation

Designing Heaven's Will: The job assignment in the Chinese imperial civil service

no code implementations6 May 2021 Inácio Bó, Li Chen

We provide an original analysis of historical documents to describe the assignment procedures used to allocate entry-level civil service jobs in China from the tenth to the early twentieth century.

Cascade Image Matting with Deformable Graph Refinement

no code implementations6 May 2021 Zijian Yu, Xuhui Li, Huijuan Huang, Wen Zheng, Li Chen

Image matting refers to the estimation of the opacity of foreground objects.

Image Matting

Hermite Polynomial-based Valuation of American Options with General Jump-Diffusion Processes

no code implementations24 Apr 2021 Li Chen, Guang Zhang

We present a new approximation scheme for the price and exercise policy of American options.

On the Robustness of Monte Carlo Dropout Trained with Noisy Labels

no code implementations22 Mar 2021 Purvi Goel, Li Chen

The memorization effect of deep learning hinders its performance to effectively generalize on test set when learning with noisy labels.

Learning with noisy labels

EXTRA: Explanation Ranking Datasets for Explainable Recommendation

1 code implementation20 Feb 2021 Lei LI, Yongfeng Zhang, Li Chen

To achieve a standard way of evaluating recommendation explanations, we provide three benchmark datasets for EXplanaTion RAnking (denoted as EXTRA), on which explainability can be measured by ranking-oriented metrics.

Recommendation Systems

Learning to Explain Recommendations

no code implementations1 Feb 2021 Lei LI, Yongfeng Zhang, Li Chen

In this paper, explaining recommendations is formulated as a ranking task, and learned from data, similar to item ranking for recommendation.

Recommendation Systems

Blind Diagnosis for Millimeter-wave Large-scale Antenna Systems

no code implementations25 Jan 2021 Rui Sun, Weidong Wang, Li Chen, Guo Wei, Wenyi Zhang

Millimeter-wave (mmWave) communication systems rely on large-scale antenna arrays to combat large path-loss at mmWave band.

Diagnosis of Intelligent Reflecting Surface in Millimeter-wave Communication Systems

1 code implementation11 Jan 2021 Rui Sun, Weidong Wang, Li Chen, Guo Wei, Wenyi Zhang

In the second case where only partial CSI is available, we jointly exploit the sparsity of the millimeter-wave channel and the failure, and adopt compressed sparse and low-rank matrix recovery algorithm to decouple channel and failure.

Robust Deep Learning with Active Noise Cancellation for Spatial Computing

no code implementations16 Nov 2020 Li Chen, David Yang, Purvi Goel, Ilknur Kabul

This paper proposes CANC, a Co-teaching Active Noise Cancellation method, applied in spatial computing to address deep learning trained with extreme noisy labels.

CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging

1 code implementation15 Oct 2020 Lei Mou, Yitian Zhao, Huazhu Fu, Yonghuai Liu, Jun Cheng, Yalin Zheng, Pan Su, Jianlong Yang, Li Chen, Alejandro F Frang, Masahiro Akiba, Jiang Liu

Automated detection of curvilinear structures, e. g., blood vessels or nerve fibres, from medical and biomedical images is a crucial early step in automatic image interpretation associated to the management of many diseases.

Automatic Label Correction for the Accurate Edge Detection of Overlapping Cervical Cells

2 code implementations5 Oct 2020 Jiawei Liu, Qiang Wang, Huijie Fan, Shuai Wang, Wentao Li, Yandong Tang, Danbo Wang, Mingyi Zhou, Li Chen

The experiments on the dataset for training show that our automatic label correction algorithm can improve the accuracy of manual labels and further improve the positioning accuracy of overlapping cells with deep learning models.

Cell Segmentation Edge Detection

RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification

no code implementations28 Sep 2020 Haifeng Li, Zhenqi Cui, Zhiqing Zhu, Li Chen, Jiawei Zhu, Haozhe Huang, Chao Tao

On the one hand, RS-MetaNet raises the level of learning from the sample to the task by organizing training in a meta way, and it learns to learn a metric space that can well classify remote sensing scenes from a series of tasks.

General Classification Metric Learning +1

Generative Model without Prior Distribution Matching

no code implementations23 Sep 2020 Cong Geng, Jia Wang, Li Chen, Zhiyong Gao

Variational Autoencoder (VAE) and its variations are classic generative models by learning a low-dimensional latent representation to satisfy some prior distribution (e. g., Gaussian distribution).

Switching Transferable Gradient Directions for Query-Efficient Black-Box Adversarial Attacks

no code implementations15 Sep 2020 Chen Ma, Shuyu Cheng, Li Chen, Jun Zhu, Junhai Yong

In each iteration, SWITCH first tries to update the current sample along the direction of $\hat{\mathbf{g}}$, but considers switching to its opposite direction $-\hat{\mathbf{g}}$ if our algorithm detects that it does not increase the value of the attack objective function.

Adversarial Attack

Simulating Unknown Target Models for Query-Efficient Black-box Attacks

1 code implementation CVPR 2021 Chen Ma, Li Chen, Jun-Hai Yong

The meta-gradients of this loss are then computed and accumulated from multiple tasks to update the Simulator and subsequently improve generalization.

Knowledge Distillation Meta-Learning

Xiaomingbot: A Multilingual Robot News Reporter

no code implementations ACL 2020 Runxin Xu, Jun Cao, Mingxuan Wang, Jiaze Chen, Hao Zhou, Ying Zeng, Yu-Ping Wang, Li Chen, Xiang Yin, Xijin Zhang, Songcheng Jiang, Yuxuan Wang, Lei LI

This paper proposes the building of Xiaomingbot, an intelligent, multilingual and multimodal software robot equipped with four integral capabilities: news generation, news translation, news reading and avatar animation.

News Generation

Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement

1 code implementation11 Jul 2020 Li Chen, Thomas Hatsukami, Jenq-Neng Hwang, Chun Yuan

Automatically labeling intracranial arteries (ICA) with their anatomical names is beneficial for feature extraction and detailed analysis of intracranial vascular structures.

Noise Robust TTS for Low Resource Speakers using Pre-trained Model and Speech Enhancement

no code implementations26 May 2020 Dongyang Dai, Li Chen, Yu-Ping Wang, Mu Wang, Rui Xia, Xuchen Song, Zhiyong Wu, Yuxuan Wang

Firstly, the speech synthesis model is pre-trained with both multi-speaker clean data and noisy augmented data; then the pre-trained model is adapted on noisy low-resource new speaker data; finally, by setting the clean speech condition, the model can synthesize the new speaker's clean voice.

Speech Enhancement Speech Synthesis

DAPnet: A Double Self-attention Convolutional Network for Point Cloud Semantic Labeling

1 code implementation18 Apr 2020 Li Chen, Zewei Xu, Yongjian Fu, Haozhe Huang, Shaowen Wang, Haifeng Li

The incorporation of the double self-attention module has an average of 7\% improvement on the pre-class accuracy.

A Survey on Conversational Recommender Systems

no code implementations1 Apr 2020 Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, Li Chen

Recommender systems are software applications that help users to find items of interest in situations of information overload.

Chatbot Recommendation Systems

Content Adaptive and Error Propagation Aware Deep Video Compression

no code implementations ECCV 2020 Guo Lu, Chunlei Cai, Xiaoyun Zhang, Li Chen, Wanli Ouyang, Dong Xu, Zhiyong Gao

Therefore, the encoder is adaptive to different video contents and achieves better compression performance by reducing the domain gap between the training and testing datasets.

Video Compression

Blurry Video Frame Interpolation

1 code implementation CVPR 2020 Wang Shen, Wenbo Bao, Guangtao Zhai, Li Chen, Xiongkuo Min, Zhiyong Gao

Existing works reduce motion blur and up-convert frame rate through two separate ways, including frame deblurring and frame interpolation.

Deblurring Video Enhancement +1

Uniform Interpolation Constrained Geodesic Learning on Data Manifold

no code implementations12 Feb 2020 Cong Geng, Jia Wang, Li Chen, Wenbo Bao, Chu Chu, Zhiyong Gao

Based on this defined Riemannian metric, we introduce a constant speed loss and a minimizing geodesic loss to regularize the interpolation network to generate uniform interpolation along the learned geodesic on the manifold.

Stable Sparse Subspace Embedding for Dimensionality Reduction

no code implementations7 Feb 2020 Li Chen, Shuizheng Zhou, Jiajun Ma

Although they adopt uniform sampling with replacement, due to large sampling variance, the number of non-zeros is uneven among rows of the projection matrix which is generated in one trial, and more data information may be lost after dimension reduction.

Dimensionality Reduction

Fast Kernel k-means Clustering Using Incomplete Cholesky Factorization

no code implementations7 Feb 2020 Li Chen, Shuisheng Zhou, Jiajun Ma

The key idea of the proposed kernel $k$-means clustering using incomplete Cholesky factorization is that we approximate the entire kernel matrix by the product of a low-rank matrix and its transposition.

Kalibre: Knowledge-based Neural Surrogate Model Calibration for Data Center Digital Twins

no code implementations29 Jan 2020 Ruihang Wang, Xin Zhou, Linsen Dong, Yonggang Wen, Rui Tan, Li Chen, Guan Wang, Feng Zeng

However, in the context of CFD, each search step requires long-lasting CFD model's iterated solving, rendering these approaches impractical with increased model complexity.

Systems and Control Systems and Control J.6; I.6.5

FFusionCGAN: An end-to-end fusion method for few-focus images using conditional GAN in cytopathological digital slides

1 code implementation3 Jan 2020 Xiebo Geng, Sibo Liua, Wei Han, Xu Li, Jiabo Ma, Jingya Yu, Xiuli Liu, Sahoqun Zeng, Li Chen, Shenghua Cheng

However, although existing image fusion techniques, including traditional algorithms and deep learning-based algorithms, can generate high-quality fused images, they need multiple images with different focus depths in the same field of view.

Semantic Segmentation whole slide images

SCAttNet: Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images

1 code implementation19 Dec 2019 Haifeng Li, Kaijian Qiu, Li Chen, Xiaoming Mei, Liang Hong, Chao Tao

High-resolution remote sensing images (HRRSIs) contain substantial ground object information, such as texture, shape, and spatial location.

Semantic Segmentation

Reversible Adversarial Attack based on Reversible Image Transformation

no code implementations6 Nov 2019 Zhaoxia Yin, Hua Wang, Li Chen, Jie Wang, Weiming Zhang

In order to prevent illegal or unauthorized access of image data such as human faces and ensure legitimate users can use authorization-protected data, reversible adversarial attack technique is rise.

Adversarial Attack Image Restoration

Robust Federated Learning with Noisy Communication

no code implementations1 Nov 2019 Fan Ang, Li Chen, Nan Zhao, Yunfei Chen, Weidong Wang, F. Richard Yu

Nevertheless, it is impractical to achieve a perfect acquisition of the local models in wireless communication due to noise, which also brings serious effects on federated learning.

Federated Learning Robust Design

Adversarial Example in Remote Sensing Image Recognition

no code implementations29 Oct 2019 Li Chen, Guowei Zhu, Qi Li, Haifeng Li

This added adversarial perturbation image is called an adversarial example, which poses a serious security problem for systems based on CNN model recognition results.

Accelerating Federated Learning via Momentum Gradient Descent

no code implementations8 Oct 2019 Wei Liu, Li Chen, Yunfei Chen, Wenyi Zhang

The proposed momentum federated learning (MFL) uses momentum gradient descent (MGD) in the local update step of FL system.

Federated Learning

Self-Paced Video Data Augmentation with Dynamic Images Generated by Generative Adversarial Networks

no code implementations16 Sep 2019 Yumeng Zhang, Gaoguo Jia, Li Chen, Mingrui Zhang, Junhai Yong

The dynamic image compresses the motion information of video into a still image, removing the interference factors such as the background.

Data Augmentation General Classification +1

Adaptive Wasserstein Hourglass for Weakly Supervised Hand Pose Estimation from Monocular RGB

no code implementations11 Sep 2019 Yumeng Zhang, Li Chen, Yufeng Liu, Junhai Yong, Wen Zheng

During training, based on the relation between these common characteristics and 3D pose learned from fully-annotated synthetic datasets, it is beneficial for the network to restore the 3D pose of weakly labeled real-world datasets with the aid of 2D annotations and depth images.

3D Hand Pose Estimation Domain Adaptation

Multi-stage domain adversarial style reconstruction for cytopathological image stain normalization

no code implementations11 Sep 2019 Xihao Chen, Jingya Yu, Li Chen, Shaoqun Zeng, Xiuli Liu, Shenghua Cheng

This article proposes a new framework that normalizes the stain style for cytopathological images through a stain removal module and a multi-stage domain adversarial style reconstruction module.

MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

1 code implementation6 Aug 2019 Chen Ma, Chenxu Zhao, Hailin Shi, Li Chen, Junhai Yong, Dan Zeng

To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples.

Adversarial Attack Detection Meta-Learning

User Validation of Recommendation Serendipity Metrics

no code implementations27 Jun 2019 Li Chen, Ningxia Wang, Yonghua Yang, Keping Yang, Quan Yuan

Though it has been recognized that recommending serendipitous (i. e., surprising and relevant) items can be helpful for increasing users' satisfaction and behavioral intention, how to measure serendipity in the offline environment is still an open issue.

An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks

no code implementations15 Jun 2019 Tianjie Mu, Xiaohui Chen, Li Chen, Huarui Yin, Weidong Wang

Deep Learning has been widely applied in the area of image processing and natural language processing.

Information Theory Signal Processing Information Theory

Sparse Representation Classification via Screening for Graphs

no code implementations4 Jun 2019 Cencheng Shen, Li Chen, Yuexiao Dong, Carey Priebe

The sparse representation classifier (SRC) is shown to work well for image recognition problems that satisfy a subspace assumption.

Classification Classification Consistency +1

Privacy Preserving Adjacency Spectral Embedding on Stochastic Blockmodels

no code implementations16 May 2019 Li Chen

For graphs generated from stochastic blockmodels, adjacency spectral embedding is asymptotically consistent.

To believe or not to believe: Validating explanation fidelity for dynamic malware analysis

no code implementations30 Apr 2019 Li Chen, Carter Yagemann, Evan Downing

For both case studies, we first train deep learning models via transfer learning on malware images, demonstrate high classification effectiveness, apply an explanation method on the images, and correlate the results back to the samples to validate whether the algorithmic insights are consistent with security domain expertise.

Classification General Classification +2

Ranking-Based Autoencoder for Extreme Multi-label Classification

no code implementations NAACL 2019 Bingyu Wang, Li Chen, Wei Sun, Kechen Qin, Kefeng Li, Hui Zhou

Extreme Multi-label classification (XML) is an important yet challenging machine learning task, that assigns to each instance its most relevant candidate labels from an extremely large label collection, where the numbers of labels, features and instances could be thousands or millions.

Classification Extreme Multi-Label Classification +3

The Efficacy of SHIELD under Different Threat Models

no code implementations1 Feb 2019 Cory Cornelius, Nilaksh Das, Shang-Tse Chen, Li Chen, Michael E. Kounavis, Duen Horng Chau

To evaluate the robustness of the defense against an adaptive attacker, we consider the targeted-attack success rate of the Projected Gradient Descent (PGD) attack, which is a strong gradient-based adversarial attack proposed in adversarial machine learning research.

Adversarial Attack Image Classification

Understanding the Importance of Single Directions via Representative Substitution

no code implementations20 Jan 2019 Li Chen, Hailun Ding, Qi Li, Zhuo Li, Jian Peng, Haifeng Li

Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior.

A Data-driven Adversarial Examples Recognition Framework via Adversarial Feature Genome

no code implementations25 Dec 2018 Li Chen, Hailun Ding, Qi Li, Jiawei Zhu, Jian Peng, Haifeng Li

Inspired by AFS, we propose a defense framework based on Adversarial Feature Genome (AFG), which can detect and correctly classify adversarial examples into original classes simultaneously.

General Classification Multi-Label Classification

Towards resilient machine learning for ransomware detection

no code implementations21 Dec 2018 Li Chen, Chih-Yuan Yang, Anindya Paul, Ravi Sahita

In this case study, we propose to use GAN to automatically produce dynamic features that exhibit generalized malicious behaviors that can reduce the efficacy of black-box ransomware classifiers.

Deep Transfer Learning for Static Malware Classification

1 code implementation18 Dec 2018 Li Chen

In the transfer learning scheme, we borrow knowledge from natural images or objects and apply to the target domain of static malware detection.

Classification General Classification +2

AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection

2 code implementations14 Dec 2018 Chen Ma, Li Chen, Junhai Yong

(2) We integrate various dynamic models (including convolutional long short-term memory, two stream network, conditional random field, and temporal action localization network) into AU R-CNN and then investigate and analyze the reason behind the performance of dynamic models.

Action Unit Detection Temporal Action Localization

Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization

no code implementations NeurIPS 2018 Yuanxiang Gao, Li Chen, Baochun Li

It is critical to place operations in a neural network on these devices in an optimal way, so that the training process can complete within the shortest amount of time.

Understanding the Importance of Single Directions via Representative Substitution

no code implementations27 Nov 2018 Li Chen, Hailun Ding, Qi Li, Zhuo Li, Jian Peng, Haifeng Li

Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior.

Spotlight: Optimizing Device Placement for Training Deep Neural Networks

no code implementations ICML 2018 Yuanxiang Gao, Li Chen, Baochun Li

Training deep neural networks (DNNs) requires an increasing amount of computation resources, and it becomes typical to use a mixture of GPU and CPU devices.

ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio

no code implementations30 May 2018 Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Li Chen, Michael E. Kounavis, Duen Horng Chau

Adversarial machine learning research has recently demonstrated the feasibility to confuse automatic speech recognition (ASR) models by introducing acoustically imperceptible perturbations to audio samples.

Adversarial Attack automatic-speech-recognition +1

Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression

3 code implementations19 Feb 2018 Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng Chau

The rapidly growing body of research in adversarial machine learning has demonstrated that deep neural networks (DNNs) are highly vulnerable to adversarially generated images.

Vertex nomination: The canonical sampling and the extended spectral nomination schemes

no code implementations14 Feb 2018 Jordan Yoder, Li Chen, Henry Pao, Eric Bridgeford, Keith Levin, Donniell Fishkind, Carey Priebe, Vince Lyzinski

There are vertex nomination schemes in the literature, including the optimally precise canonical nomination scheme~$\mathcal{L}^C$ and the consistent spectral partitioning nomination scheme~$\mathcal{L}^P$.

Stochastic Block Model

HeNet: A Deep Learning Approach on Intel$^\circledR$ Processor Trace for Effective Exploit Detection

no code implementations8 Jan 2018 Li Chen, Salmin Sultana, Ravi Sahita

The low-level model is a per-application behavior model, trained via transfer learning on a time-series of images generated from control flow trace of an execution.

Feature Engineering General Classification +3

Y-net: 3D intracranial artery segmentation using a convolutional autoencoder

no code implementations19 Dec 2017 Li Chen, Yanjun Xie, Jie Sun, Niranjan Balu, Mahmud Mossa-Basha, Kristi Pimentel, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan

Automated segmentation of intracranial arteries on magnetic resonance angiography (MRA) allows for quantification of cerebrovascular features, which provides tools for understanding aging and pathophysiological adaptations of the cerebrovascular system.

General Classification

Stochastic Variance Reduction Gradient for a Non-convex Problem Using Graduated Optimization

no code implementations10 Jul 2017 Li Chen, Shuisheng Zhou, Zhuan Zhang

Graduated Optimization Algorithm (GOA) is a popular heuristic method to obtain global optimums of nonconvex problems through progressively minimizing a series of convex approximations to the nonconvex problems more and more accurate.

Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression

no code implementations8 May 2017 Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng Chau

Deep neural networks (DNNs) have achieved great success in solving a variety of machine learning (ML) problems, especially in the domain of image recognition.

Semi-supervised classification for dynamic Android malware detection

no code implementations19 Apr 2017 Li Chen, Mingwei Zhang, Chih-Yuan Yang, Ravi Sahita

When this similarity is strong, MBSS and SVM with linear kernel maintain 90\% detection rate while $k$NN and LDA suffer great performance degradation.

Android Malware Detection Classification +2

Sparse Algorithm for Robust LSSVM in Primal Space

no code implementations7 Feb 2017 Li Chen, Shuisheng Zhou

Then approximating the kernel matrix by a low-rank matrix and smoothing the loss function by entropy penalty function, we propose a convergent sparse R-LSSVM (SR-LSSVM) algorithm to achieve the sparse solution of primal R-LSSVM, which overcomes two drawbacks of LSSVM simultaneously.

On Study of the Binarized Deep Neural Network for Image Classification

no code implementations24 Feb 2016 Song Wang, Dongchun Ren, Li Chen, Wei Fan, Jun Sun, Satoshi Naoi

Unlike those trials, in this paper, we focused on the basic propagation function of the artificial neural network and proposed the binarized deep neural network.

General Classification Image Classification

Sparse Representation Classification Beyond L1 Minimization and the Subspace Assumption

no code implementations4 Feb 2015 Cencheng Shen, Li Chen, Yuexiao Dong, Carey E. Priebe

The results are demonstrated via simulations and real data experiments, where the new algorithm achieves comparable numerical performance and significantly faster.

Classification Classification Consistency +1

Robust Vertex Classification

no code implementations23 Nov 2013 Li Chen, Cencheng Shen, Joshua Vogelstein, Carey Priebe

For random graphs distributed according to stochastic blockmodels, a special case of latent position graphs, adjacency spectral embedding followed by appropriate vertex classification is asymptotically Bayes optimal; but this approach requires knowledge of and critically depends on the model dimension.

Classification General Classification

Unsupervised deconvolution of dynamic imaging reveals intratumor vascular heterogeneity

no code implementations14 Jun 2013 Li Chen, Peter L . Choyke, Niya Wang, Robert Clarke, Zaver M. Bhujwalla, Elizabeth M. C. Hillman, Yue Wang

Intratumor heterogeneity is often manifested by vascular compartments with distinct pharmacokinetics that cannot be resolved directly by in vivo dynamic imaging.

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