Search Results for author: Chao Chen

Found 75 papers, 25 papers with code

TopoGAN: A Topology-Aware Generative Adversarial Network

no code implementations ECCV 2020 Fan Wang, Huidong Liu, Dimitris Samaras, Chao Chen

We show in experiments that our method generates synthetic images with realistic topology.

R4: A Framework for Route Representation and Route Recommendation

no code implementations20 Oct 2021 Ran Cheng, Chao Chen, Longfei Xu, Shen Li, Lei Wang, Hengbin Cui, Kaikui Liu, Xiaolong Li

For user representation, we utilize a series of historical navigation to extract user preference.

Trigger Hunting with a Topological Prior for Trojan Detection

no code implementations15 Oct 2021 Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha, Chao Chen

Despite their success and popularity, deep neural networks (DNNs) are vulnerable when facing backdoor attacks.

A Frequency-Domain Approach to Nonlinear Negative Imaginary Systems Analysis

no code implementations30 Sep 2021 Di Zhao, Chao Chen, Sei Zhen Khong

In this study, we extend the theory of negative imaginary (NI) systems to a nonlinear framework using a frequency-domain approach.

Self-learn to Explain Siamese Networks Robustly

no code implementations15 Sep 2021 Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie

Learning to compare two objects are essential in applications, such as digital forensics, face recognition, and brain network analysis, especially when labeled data is scarce and imbalanced.

Face Recognition Fairness

The Singular Angle of Nonlinear Systems

no code implementations3 Sep 2021 Chao Chen, Wei Chen, Di Zhao, Sei Zhen Khong, Li Qiu

It is, thus, different from the recently appeared nonlinear system phase which adopts the complexification of real-valued signals using the Hilbert transform.

Convolutional Block Design for Learned Fractional Downsampling

no code implementations20 May 2021 Li-Heng Chen, Christos G. Bampis, Zhi Li, Chao Chen, Alan C. Bovik

The layers of convolutional neural networks (CNNs) can be used to alter the resolution of their inputs, but the scaling factors are limited to integer values.

SSIM Video Compression

TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer

1 code implementation13 May 2021 Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, Chao Chen

Characterization of breast parenchyma on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures.

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.

Structure Guided Lane Detection

1 code implementation12 May 2021 Jinming Su, Chao Chen, Ke Zhang, Junfeng Luo, Xiaoming Wei, Xiaolin Wei

Next, multi-level structural constraints are used to improve the perception of lanes.

Autonomous Driving Lane Detection

NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering

no code implementations15 Apr 2021 Dongsheng Li, Haodong Liu, Chao Chen, Yingying Zhao, Stephen M. Chu, Bo Yang

In collaborative filtering (CF) algorithms, the optimal models are usually learned by globally minimizing the empirical risks averaged over all the observed data.

Collaborative Filtering Ensemble Learning

Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNets

1 code implementation4 Apr 2021 Chao Chen, Catalina Raymond, Bill Speier, Xinyu Jin, Timothy F. Cloughesy, Dieter Enzmann, Benjamin M. Ellingson, Corey W. Arnold

In this work, we present a deep learning based approach for contrast-enhanced T1 synthesis on brain tumor patients.

Topology-Aware Segmentation Using Discrete Morse Theory

no code implementations ICLR 2021 Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen

In the segmentation of fine-scale structures from natural and biomedical images, per-pixel accuracy is not the only metric of concern.

Semantic Segmentation

Compiler-Guided Throughput Scheduling for Many-core Machines

no code implementations11 Mar 2021 Girish Mururu, Chao Chen, Chris Porter, Santosh Pande, Ada Gavrilovska

The information produced by beacons in multiple processes is aggregated and analyzed by the proactive scheduler to respond to the anticipated workload requirements.

Distributed, Parallel, and Cluster Computing

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

1 code implementation16 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.

Stability of SGD: Tightness Analysis and Improved Bounds

no code implementations10 Feb 2021 Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami

This raises the question: is the stability analysis of [18] tight for smooth functions, and if not, for what kind of loss functions and data distributions can the stability analysis be improved?

Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach

1 code implementation9 Feb 2021 Yikai Zhang, Hui Qu, Qi Chang, Huidong Liu, Dimitris Metaxas, Chao Chen

A federatedGAN jointly trains a centralized generator and multiple private discriminators hosted at different sites.

Federated Learning

Revisiting the Stability of Stochastic Gradient Descent: A Tightness Analysis

no code implementations1 Jan 2021 Yikai Zhang, Samuel Bald, Wenjia Zhang, Vamsi Pritham Pingali, Chao Chen, Mayank Goswami

We provide empirical evidence that this condition holds for several loss functions, and provide theoretical evidence that the known tight SGD stability bounds for convex and non-convex loss functions can be circumvented by HC loss functions, thus partially explaining the generalization of deep neural networks.

Exponential degradation

Ricci-GNN: Defending Against Structural Attacks Through a Geometric Approach

no code implementations1 Jan 2021 Ze Ye, Tengfei Ma, Chien-Chun Ni, Kin Sum Liu, Jie Gao, Chao Chen

We propose a novel GNN defense algorithm against structural attacks that maliciously modify graph topology.

Unsupervised Learning of Fine Structure Generation for 3D Point Clouds by 2D Projections Matching

1 code implementation ICCV 2021 Chao Chen, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker

Our method pushes the neural network to generate a 3D point cloud whose 2D projections match the irregular point supervision from different view angles.

Point Cloud Generation

Localization in the Crowd with Topological Constraints

1 code implementation23 Dec 2020 Shahira Abousamra, Minh Hoai, Dimitris Samaras, Chao Chen

Due to various challenges, a localization method is prone to spatial semantic errors, i. e., predicting multiple dots within a same person or collapsing multiple dots in a cluttered region.

Crowd Counting

Phase of Nonlinear Systems

no code implementations30 Nov 2020 Chao Chen, Di Zhao, Wei Chen, Sei Zhen Khong, Li Qiu

A nonlinear small phase theorem is then established for feedback stability analysis of semi-sectorial systems.

Error-Bounded Correction of Noisy Labels

3 code implementations ICML 2020 Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen

To be robust against label noise, many successful methods rely on the noisy classifiers (i. e., models trained on the noisy training data) to determine whether a label is trustworthy.

Image Classification

RCHOL: Randomized Cholesky Factorization for Solving SDD Linear Systems

2 code implementations16 Nov 2020 Chao Chen, Tianyu Liang, George Biros

We introduce a randomized algorithm, namely RCHOL, to construct an approximate Cholesky factorization for a given Laplacian matrix (a. k. a., graph Laplacian).

Numerical Analysis Mathematical Software Numerical Analysis

Minimizing Labeling Effort for Tree Skeleton Segmentation using an Automated Iterative Training Methodology

no code implementations16 Oct 2020 Keenan Granland, Rhys Newbury, David Ting, Chao Chen

It is shown that in our application, the new Automating-the-Loop method greatly reduces the labeling effort while producing comparable performance to both human-in-the-loop and complete manual labeling methods.

Semantic Segmentation

Semantic Segmentation for Partially Occluded Apple Trees Based on Deep Learning

no code implementations14 Oct 2020 Zijue Chen, David Ting, Rhys Newbury, Chao Chen

DeepLabv3 outperforms the other models at Binary accuracy, Mean IoU and Boundary F1 score, but is surpassed by Pix2Pix (without discriminator) and U-Net in Occluded branch recall.

Semantic Segmentation

Deep Variational Instance Segmentation

1 code implementation NeurIPS 2020 Jialin Yuan, Chao Chen, Li Fuxin

Specifically, we propose a variational relaxation of instance segmentation as minimizing an optimization functional for a piecewise-constant segmentation problem, which can be used to train an FCN end-to-end.

Instance Segmentation Semantic Segmentation

Object Tracking by Least Spatiotemporal Searches

no code implementations18 Jul 2020 Zhiyong Yu, Lei Han, Chao Chen, Wenzhong Guo, Zhiwen Yu

This paper proposes a strategy named IHMs (Intermediate Searching at Heuristic Moments): each step we figure out which moment is the best to search according to a heuristic indicator, then at that moment search locations one by one in descending order of predicted appearing probabilities, until a search hits; iterate this step until we get the object's current location.

Object Tracking

Learn distributed GAN with Temporary Discriminators

1 code implementation ECCV 2020 Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas

Our proposed method tackles the challenge of training GAN in the federated learning manner: How to update the generator with a flow of temporary discriminators?

Federated Learning

DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images

no code implementations ICML 2020 Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker

To optimize 3D shape parameters, current renderers rely on pixel-wise losses between rendered images of 3D reconstructions and ground truth images from corresponding viewpoints.

End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19

no code implementations28 Jun 2020 Abdelkader Nasreddine Belkacem, Sofia Ouhbi, Abderrahmane Lakas, Elhadj Benkhelifa, Chao Chen

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus.

Local Causal Structure Learning and its Discovery Between Type 2 Diabetes and Bone Mineral Density

no code implementations27 Jun 2020 Wei Wang, Gangqiang Hu, Bo Yuan, Shandong Ye, Chao Chen, YaYun Cui, Xi Zhang, Liting Qian

To illustrate the importance of prior knowledge, the result of the algorithm without prior knowledge is also investigated.

Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment

1 code implementation30 May 2020 Chao Chen, Zhihong Chen, Xinyu Jin, Lanjuan Li, William Speier, Corey W. Arnold

However, training with the global image underutilizes discriminative local information, while providing extra annotations is expensive and subjective.

Age Estimation

Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data

1 code implementation CVPR 2020 Qi Chang, Hui Qu, Yikai Zhang, Mert Sabuncu, Chao Chen, Tong Zhang, Dimitris Metaxas

In this paper, we propose a data privacy-preserving and communication efficient distributed GAN learning framework named Distributed Asynchronized Discriminator GAN (AsynDGAN).

Rigorous Explanation of Inference on Probabilistic Graphical Models

no code implementations21 Apr 2020 Yifei Liu, Chao Chen, Xi Zhang, Sihong Xie

There is no existing method to rigorously attribute the inference outcomes to the contributing factors of the graphical models.

Decision Making

Real-Time Fruit Recognition and Grasping Estimation for Autonomous Apple Harvesting

no code implementations30 Mar 2020 Hanwen Kang, Chao Chen

In this research, a fully neural network based visual perception framework for autonomous apple harvesting is proposed.

Instance Segmentation Robotic Grasping +1

Visual Perception and Modelling in Unstructured Orchard for Apple Harvesting Robots

no code implementations29 Dec 2019 Hanwen Kang, Chao Chen

This paper develops a framework of visual perception and modelling for robotic harvesting of fruits in the orchard environments.

Pose Estimation

HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation

1 code implementation27 Dec 2019 Chao Chen, Zhihang Fu, Zhihong Chen, Sheng Jin, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua

In particular, our proposed HoMM can perform arbitrary-order moment tensor matching, we show that the first-order HoMM is equivalent to Maximum Mean Discrepancy (MMD) and the second-order HoMM is equivalent to Correlation Alignment (CORAL).

Unsupervised Domain Adaptation

Fruit Detection, Segmentation and 3D Visualisation of Environments in Apple Orchards

no code implementations28 Nov 2019 Hanwen Kang, Chao Chen

The robustness and efficiency of the DaSNet-V2 in detection and segmentation are validated by the experiments in the real-environment of apple orchard.

Instance Segmentation Semantic Segmentation

Point Cloud Processing via Recurrent Set Encoding

no code implementations25 Nov 2019 Pengxiang Wu, Chao Chen, Jingru Yi, Dimitris Metaxas

The spatial layout of the beams is regular, and this allows the beam features to be further fed into an efficient 2D convolutional neural network (CNN) for hierarchical feature aggregation.

SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation

no code implementations20 Nov 2019 Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xian-Sheng Hua

In this paper, we propose a novel Semi-supervised Self-pace Adversarial Hashing method, named SSAH to solve the above problems in a unified framework.

A Predictive On-Demand Placement of UAV Base Stations Using Echo State Network

no code implementations25 Sep 2019 Haoran Peng, Chao Chen, Chuan-Chi Lai, Li-Chun Wang, Zhu Han

In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories.

Scalable Explanation of Inferences on Large Graphs

no code implementations13 Aug 2019 Chao Chen, Yifei Liu, Xi Zhang, Sihong Xie

Probabilistic inferences distill knowledge from graphs to aid human make important decisions.

ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences

no code implementations31 Jul 2019 Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker

Specifically, ShapeCaptioner aggregates the parts detected in multiple colored views using our novel part class specific aggregation to represent a 3D shape, and then, employs a sequence to sequence model to generate the caption.

Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types

no code implementations9 Jul 2019 Shahira Abousamra, Le Hou, Rajarsi Gupta, Chao Chen, Dimitris Samaras, Tahsin Kurc, Rebecca Batiste, Tianhao Zhao, Shroyer Kenneth, Joel Saltz

This allows for a much larger training set, that reflects visual variability across multiple cancer types and thus training of a single network which can be automatically applied to each cancer type without human adjustment.

General Classification

DeepSquare: Boosting the Learning Power of Deep Convolutional Neural Networks with Elementwise Square Operators

no code implementations12 Jun 2019 Sheng Chen, Xu Wang, Chao Chen, Yifan Lu, Xijin Zhang, Linfu Wen

In this paper, we pursue very efficient neural network modules which can significantly boost the learning power of deep convolutional neural networks with negligible extra computational cost.

Topology-Preserving Deep Image Segmentation

1 code implementation NeurIPS 2019 Xiaoling Hu, Li Fuxin, Dimitris Samaras, Chao Chen

Segmentation algorithms are prone to make topological errors on fine-scale structures, e. g., broken connections.

Semantic Segmentation

Automatic Long-Term Deception Detection in Group Interaction Videos

no code implementations15 May 2019 Chongyang Bai, Maksim Bolonkin, Judee Burgoon, Chao Chen, Norah Dunbar, Bharat Singh, V. S. Subrahmanian, Zhe Wu

Most work on automated deception detection (ADD) in video has two restrictions: (i) it focuses on a video of one person, and (ii) it focuses on a single act of deception in a one or two minute video.

Deception Detection

Strain engineering of epitaxial oxide heterostructures beyond substrate limitations

no code implementations3 May 2019 Xiong Deng, Chao Chen, Deyang Chen, Xiangbin Cai, Xiaozhe Yin, Chao Xu, Fei Sun, Caiwen Li, Yan Li, Han Xu, Mao Ye, Guo Tian, Zhen Fan, Zhipeng Hou, Minghui Qin, Yu Chen, Zhenlin Luo, Xubing Lu, Guofu Zhou, Lang Chen, Ning Wang, Ye Zhu, Xingsen Gao, Jun-Ming Liu

The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering for further exploring novel properties and exhaustively studying fundamental physics in complex oxides.

Materials Science

Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation

no code implementations13 Apr 2019 Chao Chen, Zhihang Fu, Zhihong Chen, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua

Recent advances in unsupervised domain adaptation mainly focus on learning shared representations by global distribution alignment without considering class information across domains.

Unsupervised Domain Adaptation

PBBFMM3D: a parallel black-box algorithm for kernel matrix-vector multiplication

3 code implementations6 Mar 2019 Ruoxi Wang, Chao Chen, Jonghyun Lee, Eric Darve

We introduce a parallel method that provably requires $O(N)$ operations to reduce the computation cost.

Mathematical Software

An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations

1 code implementation9 Jan 2019 Léopold Cambier, Chao Chen, Erik G Boman, Sivasankaran Rajamanickam, Raymond S. Tuminaro, Eric Darve

We evaluate the algorithm on some large problems show it exhibits near-linear scaling.

Numerical Analysis

Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions

no code implementations11 Dec 2018 Weikai Chen, Xiaoguang Han, Guanbin Li, Chao Chen, Jun Xing, Yajie Zhao, Hao Li

Three-dimensional object recognition has recently achieved great progress thanks to the development of effective point cloud-based learning frameworks, such as PointNet and its extensions.

3D Object Recognition

Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis

no code implementations20 Nov 2018 Chao Chen, Sheng Zhang, Cuibing Du

Change detection has been a challenging visual task due to the dynamic nature of real-world scenes.

Data Augmentation

Collaborative Filtering with Stability

no code implementations6 Nov 2018 Dongsheng Li, Chao Chen, Qin Lv, Junchi Yan, Li Shang, Stephen M. Chu

Collaborative filtering (CF) is a popular technique in today's recommender systems, and matrix approximation-based CF methods have achieved great success in both rating prediction and top-N recommendation tasks.

Collaborative Filtering Recommendation Systems

Parameter Transfer Extreme Learning Machine based on Projective Model

1 code implementation4 Sep 2018 Chao Chen, Boyuan Jiang, Xinyu Jin

Unlike the existing parameter transfer approaches, which incorporate the source model information into the target by regularizing the di erence between the source and target domain parameters, an intuitively appealing projective-model is proposed to bridge the source and target model parameters.

Domain Adaptation Feature Selection +1

Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation

1 code implementation28 Aug 2018 Chao Chen, Zhihong Chen, Boyuan Jiang, Xinyu Jin

Recently, considerable effort has been devoted to deep domain adaptation in computer vision and machine learning communities.

Domain Adaptation

A Topological Regularizer for Classifiers via Persistent Homology

no code implementations27 Jun 2018 Chao Chen, Xiuyan Ni, Qinxun Bai, Yusu Wang

In particular, our measurement of topological complexity incorporates the importance of topological features (e. g., connected components, handles, and so on) in a meaningful manner, and provides a direct control over spurious topological structures.

An Approximate Bayesian Long Short-Term Memory Algorithm for Outlier Detection

no code implementations23 Dec 2017 Chao Chen, Xiao Lin, Gabriel Terejanu

In this study, we propose an approximate estimation of the weights uncertainty using Ensemble Kalman Filter, which is easily scalable to a large number of weights.

Outlier Detection

Mixture-Rank Matrix Approximation for Collaborative Filtering

no code implementations NeurIPS 2017 Dongsheng Li, Chao Chen, Wei Liu, Tun Lu, Ning Gu, Stephen Chu

However, our studies show that submatrices with different ranks could coexist in the same user-item rating matrix, so that approximations with fixed ranks cannot perfectly describe the internal structures of the rating matrix, therefore leading to inferior recommendation accuracy.

Collaborative Filtering

Multiple Instance Hybrid Estimator for Hyperspectral Target Characterization and Sub-pixel Target Detection

no code implementations31 Oct 2017 Changzhe Jiao, Chao Chen, Ronald G. McGarvey, Stephanie Bohlman, Licheng Jiao, Alina Zare

The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented.

Multiple Instance Learning

Partial Membership Latent Dirichlet Allocation

2 code implementations28 Dec 2016 Chao Chen, Alina Zare, Huy Trinh, Gbeng Omotara, J. Tory Cobb, Timotius Lagaunne

Topic models (e. g., pLSA, LDA, sLDA) have been widely used for segmenting imagery.

Topic Models

Partial Membership Latent Dirichlet Allocation

2 code implementations9 Nov 2015 Chao Chen, Alina Zare, J. Tory Cobb

Topic models (e. g., pLSA, LDA, SLDA) have been widely used for segmenting imagery.

Topic Models

Mode Estimation for High Dimensional Discrete Tree Graphical Models

no code implementations NeurIPS 2014 Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao

Though the mode finding problem is generally intractable in high dimensions, this paper unveils that, if the distribution can be approximated well by a tree graphical model, mode characterization is significantly easier.

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