Search Results for author: Chen Wang

Found 110 papers, 35 papers with code

DeepPortraitDrawing: Generating Human Body Images from Freehand Sketches

no code implementations4 May 2022 Xian Wu, Chen Wang, Hongbo Fu, Ariel Shamir, Song-Hai Zhang, Shi-Min Hu

Researchers have explored various ways to generate realistic images from freehand sketches, e. g., for objects and human faces.

Image Generation Sketch-to-Image Translation

Prediction and Control of Focal Seizure Spread: Random Walk with Restart on Heterogeneous Brain Networks

no code implementations14 Apr 2022 Chen Wang, Sida Chen, Liang Huang, Lianchun Yu

In this study, we used a whole-brain model to show that heterogeneity in nodal excitability had a significant impact on seizure propagation in the networks, and compromised the prediction accuracy with structural connections.

Learning and Transferring Value Function for Robot Exploration in Subterranean Environments

no code implementations7 Apr 2022 Yafei Hu, Chen Wang, John Keller, Sebastian Scherer

To the best of our knowledge, this work for the first time demonstrates value function prediction with previous collected datasets to help exploration in challenging subterranean environments.

Revisiting Neighborhood-based Link Prediction for Collaborative Filtering

no code implementations29 Mar 2022 Hao-Ming Fu, Patrick Poirson, Kwot Sin Lee, Chen Wang

While there is a rich literature of such works using advanced models for learning user and item representations separately, item recommendation is essentially a link prediction problem between users and items.

Collaborative Filtering Link Prediction +1

Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective

1 code implementation21 Mar 2022 Jiawei Zhang, Xiang Wang, Xiao Bai, Chen Wang, Lei Huang, Yimin Chen, Lin Gu, Jun Zhou, Tatsuya Harada, Edwin R. Hancock

The stereo contrastive feature loss function explicitly constrains the consistency between learned features of matching pixel pairs which are observations of the same 3D points.

Contrastive Learning Stereo Matching

Pursuit-evasion differential games of players with different speeds in spaces of different dimensions

no code implementations28 Feb 2022 Shuai Li, Chen Wang, Guangming Xie

We study pursuit-evasion differential games between a faster pursuer moving in 3D space and an evader moving in a plane.

Identifying Oscillations Injected by Inverter-Based Solar Energy Sources

no code implementations23 Feb 2022 Chen Wang, Luigi Vanfretti, Chetan Mishra, Kevin D. Jones, R. Matthew Gardner

This new mode was recognized from the analysis of real-world ambient synchrophasor and point-of-wave data.

SADN: Learned Light Field Image Compression with Spatial-Angular Decorrelation

no code implementations22 Feb 2022 Kedeng Tong, Xin Jin, Chen Wang, Fan Jiang

Light field image becomes one of the most promising media types for immersive video applications.

Image Compression

Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network

1 code implementation7 Feb 2022 Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu

We conduct a comprehensive analysis of users' online game behaviors, which motivates the necessity of handling those three characteristics in the online game recommendation.

Recommendation Systems

NeRF-SR: High-Quality Neural Radiance Fields using Super-Sampling

no code implementations3 Dec 2021 Chen Wang, Xian Wu, Yuan-Chen Guo, Song-Hai Zhang, Yu-Wing Tai, Shi-Min Hu

We present NeRF-SR, a solution for high-resolution (HR) novel view synthesis with mostly low-resolution (LR) inputs.

Novel View Synthesis

AirObject: A Temporally Evolving Graph Embedding for Object Identification

1 code implementation30 Nov 2021 Nikhil Varma Keetha, Chen Wang, Yuheng Qiu, Kuan Xu, Sebastian Scherer

In this context, we propose a novel temporal 3D object encoding approach, dubbed AirObject, to obtain global keypoint graph-based embeddings of objects.

Frame Graph Attention +2

Unsupervised Online Learning for Robotic Interestingness with Visual Memory

1 code implementation18 Nov 2021 Chen Wang, Yuheng Qiu, Wenshan Wang, Yafei Hu, Seungchan Kim, Sebastian Scherer

Instead, we propose to develop a method that automatically adapts online to the environment to report interesting scenes quickly.

online learning Translation

Pre-training Graph Neural Network for Cross Domain Recommendation

no code implementations16 Nov 2021 Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu

Then, we transfer the pre-trained graph encoder to initialize the node embeddings on the target domain, which benefits the fine-tuning of the single domain recommender system on the target domain.

Graph Representation Learning Recommendation Systems

Cycle-Balanced Representation Learning For Counterfactual Inference

no code implementations29 Oct 2021 Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu

With the widespread accumulation of observational data, researchers obtain a new direction to learn counterfactual effects in many domains (e. g., health care and computational advertising) without Randomized Controlled Trials(RCTs).

Counterfactual Inference Domain Adaptation +1

Pseudo Supervised Monocular Depth Estimation with Teacher-Student Network

no code implementations22 Oct 2021 Huan Liu, Junsong Yuan, Chen Wang, Jun Chen

Despite recent improvement of supervised monocular depth estimation, the lack of high quality pixel-wise ground truth annotations has become a major hurdle for further progress.

Knowledge Distillation Monocular Depth Estimation

Deep Fraud Detection on Non-attributed Graph

no code implementations4 Oct 2021 Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu

The successes of most previous methods heavily rely on rich node features and high-fidelity labels.

Contrastive Learning Fraud Detection

Sublinear Time and Space Algorithms for Correlation Clustering via Sparse-Dense Decompositions

no code implementations29 Sep 2021 Sepehr Assadi, Chen Wang

We present a new approach for solving (minimum disagreement) correlation clustering that results in sublinear algorithms with highly efficient time and space complexity for this problem.

Single Person Pose Estimation: A Survey

no code implementations21 Sep 2021 Feng Zhang, Xiatian Zhu, Chen Wang

Human pose estimation in unconstrained images and videos is a fundamental computer vision task.

Data Augmentation Pose Estimation

AirDOS: Dynamic SLAM benefits from Articulated Objects

1 code implementation21 Sep 2021 Yuheng Qiu, Chen Wang, Wenshan Wang, Mina Henein, Sebastian Scherer

To the best of our knowledge, AirDOS is the first dynamic object-aware SLAM system demonstrating that camera pose estimation can be improved by incorporating dynamic articulated objects.

Motion Estimation Pose Estimation

Low-resolution Human Pose Estimation

no code implementations19 Sep 2021 Chen Wang, Feng Zhang, Xiatian Zhu, Shuzhi Sam Ge

Human pose estimation has achieved significant progress on images with high imaging resolution.

Pose Estimation

AirLoop: Lifelong Loop Closure Detection

1 code implementation18 Sep 2021 Dasong Gao, Chen Wang, Sebastian Scherer

Nevertheless, simply finetuning the model on new data is infeasible since it may cause the model's performance on previously learned data to degrade over time, which is also known as the problem of catastrophic forgetting.

Incremental Learning Loop Closure Detection +1

Blockchain-based Trustworthy Federated Learning Architecture

no code implementations16 Aug 2021 Sin Kit Lo, Yue Liu, Qinghua Lu, Chen Wang, Xiwei Xu, Hye-Young Paik, Liming Zhu

To enhance the accountability and fairness of federated learning systems, we present a blockchain-based trustworthy federated learning architecture.

Fairness Federated Learning

Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration

1 code implementation13 Aug 2021 Chen Wang, Claudia Pérez-D'Arpino, Danfei Xu, Li Fei-Fei, C. Karen Liu, Silvio Savarese

Our method co-optimizes a human policy and a robot policy in an interactive learning process: the human policy learns to generate diverse and plausible collaborative behaviors from demonstrations while the robot policy learns to assist by estimating the unobserved latent strategy of its human collaborator.

What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

1 code implementation6 Aug 2021 Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín

Based on the study, we derive a series of lessons including the sensitivity to different algorithmic design choices, the dependence on the quality of the demonstrations, and the variability based on the stopping criteria due to the different objectives in training and evaluation.

Imitation Learning reinforcement-learning

Interpreting Depression From Question-wise Long-term Video Recording of SDS Evaluation

no code implementations25 Jun 2021 Wanqing Xie, Lizhong Liang, Yao Lu, Chen Wang, Jihong Shen, Hui Luo, Xiaofeng Liu

To automatically interpret depression from the SDS evaluation and the paired video, we propose an end-to-end hierarchical framework for the long-term variable-length video, which is also conditioned on the questionnaire results and the answering time.

Depression Detection

Learning Implicit Glyph Shape Representation

no code implementations16 Jun 2021 Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li, Chen Wang, Song-Hai Zhang

In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph images at arbitrary high resolutions.

Font Style Transfer Vector Graphics

Spatial-temporal Conv-sequence Learning with Accident Encoding for Traffic Flow Prediction

no code implementations21 May 2021 Zichuan Liu, Rui Zhang, Chen Wang, Zhu Xiao, Hongbo Jiang

In an intelligent transportation system, the key problem of traffic forecasting is how to extract periodic temporal dependencies and complex spatial correlations.

De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks

no code implementations8 May 2021 Jian Chen, Xuxin Zhang, Rui Zhang, Chen Wang, Ling Liu

The results demonstrate that De-Pois is effective and efficient for detecting poisoned data against all the four types of poisoning attacks, with both the accuracy and F1-score over 0. 9 on average.

Data Augmentation Data Poisoning

Robust Sensor Fusion Algorithms Against Voice Command Attacks in Autonomous Vehicles

1 code implementation20 Apr 2021 Jiwei Guan, Xi Zheng, Chen Wang, Yipeng Zhou, Alireza Jolfa

This technology enables drivers to use voice commands to control the vehicle and will be soon available in Advanced Driver Assistance Systems (ADAS).

Autonomous Driving Multimodal Deep Learning

Few-Shot Meta-Learning on Point Cloud for Semantic Segmentation

no code implementations7 Apr 2021 Xudong Li, Li Feng, Lei LI, Chen Wang

With a good understanding of environmental information, construction robots can work better.

Autonomous Driving Meta-Learning +1

Decentralized Circle Formation Control for Fish-like Robots in the Real-world via Reinforcement Learning

no code implementations9 Mar 2021 Tianhao Zhang, Yueheng Li, Shuai Li, Qiwei Ye, Chen Wang, Guangming Xie

In this paper, the circle formation control problem is addressed for a group of cooperative underactuated fish-like robots involving unknown nonlinear dynamics and disturbances.


Human-Understandable Decision Making for Visual Recognition

no code implementations5 Mar 2021 Xiaowei Zhou, Jie Yin, Ivor Tsang, Chen Wang

The widespread use of deep neural networks has achieved substantial success in many tasks.

Decision Making

A parametric congruence arising from Orr's identity

no code implementations4 Mar 2021 Chen Wang, Zhi-Wei Sun

Then for $\alpha, z\in\mathbb{Z}_p$ with $\langle -\alpha\rangle_p\equiv0\pmod{2}$ we mainly prove the following congruence arising from Orr's identity: $$ {}_2F_1\bigg[\begin{matrix}\frac12\alpha&\frac32-\frac12\alpha\\ &1\end{matrix}\bigg|z\bigg]_{p-1}{}_2F_1\bigg[\begin{matrix}\frac12\alpha&\frac12-\frac12\alpha\\ &1\end{matrix}\bigg|z\bigg]_{p-1}\equiv{}_3F_2\bigg[\begin{matrix}\alpha&2-\alpha&\frac12\\ &1&1\end{matrix}\bigg|z\bigg]_{p-1}\pmod{p^2}, $$ where $\langle x\rangle_p$ denotes the least nonnegative residue of $x$ modulo $p$ for any $x\in\mathbb{Z}_p$.

Number Theory Combinatorics 11A07, 33C20, 11B65, 05A10

Generalization Through Hand-Eye Coordination: An Action Space for Learning Spatially-Invariant Visuomotor Control

no code implementations28 Feb 2021 Chen Wang, Rui Wang, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese, Danfei Xu

Key to such capability is hand-eye coordination, a cognitive ability that enables humans to adaptively direct their movements at task-relevant objects and be invariant to the objects' absolute spatial location.

Imitation Learning

Learning Purified Feature Representations from Task-irrelevant Labels

no code implementations22 Feb 2021 Yinghui Li, Chen Wang, Li Yangning, Ning Ding, Hai-Tao Zheng

Learning an empirically effective model with generalization using limited data is a challenging task for deep neural networks.

ScalingNet: extracting features from raw EEG data for emotion recognition

no code implementations7 Feb 2021 Jingzhao Hu, Chen Wang, Qiaomei Jia, Qirong Bu, Jun Feng

Convolutional Neural Networks(CNNs) has achieved remarkable performance breakthrough in a variety of tasks.

EEG Emotion Recognition

Lookup subnet based Spatial Graph Convolutional neural Network

no code implementations4 Feb 2021 Jingzhao Hu, Xiaoqi Zhang, Qiaomei Jia, Chen Wang, Qirong Bu, Jun Feng

Convolutional Neural Networks(CNNs) has achieved remarkable performance breakthrough in Euclidean structure data.

An Improved Level Set Method for Reachability Problems in Differential Games

no code implementations24 Jan 2021 Wei Liao, Taotao Liang, Pengwen Xiong, Chen Wang, Aiguo Song, Peter X. Liu

The reachable tube is described as a sublevel set of a value function, which is the viscosity solution of a Hamilton-Jacobi equation with running cost.

Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features

no code implementations14 Jan 2021 David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen

We applied and compared eight GNN models including AGNN, ChebNet, GAT, GCN, GIN, GraphSAGE, SGC, and TAGCN on the Mayo Clinic cancer disease dataset and assessedtheir performance as well as compared them with each other and with more conventional machinelearning models such as decision tree, gradient boosting, multi-layer perceptron, naive bayes, andrandom forest which we used as the baselines.

Architectural Patterns for the Design of Federated Learning Systems

no code implementations7 Jan 2021 Sin Kit Lo, Qinghua Lu, Liming Zhu, Hye-Young Paik, Xiwei Xu, Chen Wang

Therefore, in this paper, we present a collection of architectural patterns to deal with the design challenges of federated learning systems.

Federated Learning

FSV: Learning to Factorize Soft Value Function for Cooperative Multi-Agent Reinforcement Learning

no code implementations1 Jan 2021 Yueheng Li, Tianhao Zhang, Chen Wang, Jinan Sun, Shikun Zhang, Guangming Xie

We explore energy-based solutions for cooperative multi-agent reinforcement learning (MARL) using the idea of function factorization in centralized training with decentralized execution (CTDE).

Multi-agent Reinforcement Learning reinforcement-learning +2

Bridging Graph Network to Lifelong Learning with Feature Interaction

no code implementations1 Jan 2021 Chen Wang, Yuheng Qiu, Sebastian Scherer

In this paper, we aim to bridge GNN to lifelong learning, which is to overcome the effect of ``catastrophic forgetting" for continuously learning a sequence of graph-structured tasks.

Graph Classification Node Classification

Federated Unlearning

no code implementations27 Dec 2020 Gaoyang Liu, Xiaoqiang Ma, Yang Yang, Chen Wang, Jiangchuan Liu

In this paper, we take the first step to fill this gap by presenting FedEraser, the first federated unlearning methodology that can eliminate the influence of a federated client's data on the global FL model while significantly reducing the time used for constructing the unlearned FL model. The basic idea of FedEraser is to trade the central server's storage for unlearned model's construction time, where FedEraser reconstructs the unlearned model by leveraging the historical parameter updates of federated clients that have been retained at the central server during the training process of FL.

Data Poisoning Federated Learning

Distances to molecular clouds in the second Galactic quadrant

no code implementations17 Dec 2020 Qing-Zeng Yan, Ji Yang, Yan Sun, Yang Su, Ye Xu, Hongchi Wang, Xin Zhou, Chen Wang

We present distances to 76 medium-sized molecular clouds and an extra large-scale one in the second Galactic quadrant ($104. 75^\circ <l<150. 25^\circ $ and $|b|<5. 25^\circ$), 73 of which are accurately measured for the first time.

Astrophysics of Galaxies

Schema Extraction on Semi-structured Data

no code implementations15 Dec 2020 Panpan Li, Yikun Gong, Chen Wang

The schemas obtained by the structural methods are more interpretable, and the statistical methods have better applicability and generalization ability.

Congruences concerning generalized central trinomial coefficients

no code implementations8 Dec 2020 Jia-Yu Chen, Chen Wang

For any $n\in\mathbb{N}=\{0, 1, 2,\ldots\}$ and $b, c\in\mathbb{Z}$, the generalized central trinomial coefficient $T_n(b, c)$ denotes the coefficient of $x^n$ in the expansion of $(x^2+bx+c)^n$.

Number Theory Combinatorics 11A07, 11B75, 11B65, 05A10

Spin-Wave Doppler Shift by Magnon Drag in Magnetic Insulators

no code implementations30 Nov 2020 Tao Yu, Chen Wang, Michael A. Sentef, Gerrit E. W. Bauer

The Doppler shift of the quasiparticle dispersion by charge currents is responsible for the critical supercurrents in superconductors and instabilities of the magnetic ground state of metallic ferromagnets.

Mesoscale and Nanoscale Physics

Object-centered image stitching

no code implementations ECCV 2018 Charles Herrmann, Chen Wang, Richard Strong Bowen, Emil Keyder, Ramin Zabih

Image stitching is typically decomposed into three phases: registration, which aligns the source images with a common target image; seam finding, which determines for each target pixel the source image it should come from; and blending, which smooths transitions over the seams.

Image Stitching Object Detection

Robust image stitching with multiple registrations

no code implementations ECCV 2018 Charles Herrmann, Chen Wang, Richard Strong Bowen, Emil Keyder, Michael Krainin, Ce Liu, Ramin Zabih

Here, we observe that the use of a single registration often leads to errors, especially in scenes with significant depth variation or object motion.

Image Stitching

Time Series Data Imputation: A Survey on Deep Learning Approaches

no code implementations23 Nov 2020 Chenguang Fang, Chen Wang

Time series methods based on deep learning have made progress with the usage of models like RNN, since it captures time information from data.

Imputation Time Series

HMFlow: Hybrid Matching Optical Flow Network for Small and Fast-Moving Objects

no code implementations19 Nov 2020 Suihanjin Yu, Youmin Zhang, Chen Wang, Xiao Bai, Liang Zhang, Edwin R. Hancock

To address this problem, we introduce a lightweight but effective Global Matching Component (GMC) to grab global matching features.

Optical Flow Estimation

On the Global Self-attention Mechanism for Graph Convolutional Networks

no code implementations21 Oct 2020 Chen Wang, Chengyuan Deng

Applying Global Self-attention (GSA) mechanism over features has achieved remarkable success on Convolutional Neural Networks (CNNs).

Can Steering Wheel Detect Your Driving Fatigue?

no code implementations18 Oct 2020 Jianchao Lu, Xi Zheng, Tianyi Zhang, Michael Sheng, Chen Wang, Jiong Jin, Shui Yu, Wanlei Zhou

In this paper, we propose a novel driver fatigue detection method by embedding surface electromyography (sEMG) sensors on a steering wheel.

Attn-HybridNet: Improving Discriminability of Hybrid Features with Attention Fusion

2 code implementations13 Oct 2020 Sunny Verma, Chen Wang, Liming Zhu, Wei Liu

The principal component analysis network (PCANet) is an unsupervised parsimonious deep network, utilizing principal components as filters in its convolution layers.

Lifelong Graph Learning

2 code implementations1 Sep 2020 Chen Wang, Yuheng Qiu, Dasong Gao, Sebastian Scherer

In this paper, we bridge GNN and lifelong learning by converting a continual graph learning problem to a regular graph learning problem so GNN can inherit the lifelong learning techniques developed for convolutional neural networks (CNN).

Action Recognition Continual Learning +3

Online Visual Place Recognition via Saliency Re-identification

1 code implementation29 Jul 2020 Han Wang, Chen Wang, Lihua Xie

As an essential component of visual simultaneous localization and mapping (SLAM), place recognition is crucial for robot navigation and autonomous driving.

Autonomous Driving Robot Navigation +3

A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective

no code implementations22 Jul 2020 Sin Kit Lo, Qinghua Lu, Chen Wang, Hye-Young Paik, Liming Zhu

Federated learning is an emerging machine learning paradigm where clients train models locally and formulate a global model based on the local model updates.

Federated Learning

Multi-Agent Reinforcement Learning in a Realistic Limit Order Book Market Simulation

no code implementations10 Jun 2020 Michaël Karpe, Jin Fang, Zhongyao Ma, Chen Wang

Optimal order execution is widely studied by industry practitioners and academic researchers because it determines the profitability of investment decisions and high-level trading strategies, particularly those involving large volumes of orders.

Multi-agent Reinforcement Learning Q-Learning +1

Supervised Contrastive Learning

16 code implementations NeurIPS 2020 Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan

Contrastive learning applied to self-supervised representation learning has seen a resurgence in recent years, leading to state of the art performance in the unsupervised training of deep image models.

Contrastive Learning Data Augmentation +3

Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks

no code implementations Elsevier Applied Energy 2020 Peng Kou, Deliang Liang, Chen Wang, Zihao Wu, Lin Gaoa

In this scheme, the optimal voltage control problem is formulated as a constrained Markov decision process, in which both state and action spaces are continuous.

reinforcement-learning Safe Exploration

Exploration with Limited Memory: Streaming Algorithms for Coin Tossing, Noisy Comparisons, and Multi-Armed Bandits

no code implementations9 Apr 2020 Sepehr Assadi, Chen Wang

In particular, algorithms with optimal sample complexity (number of coin tosses) have been known for this problem for quite some time.

Multi-Armed Bandits

TartanAir: A Dataset to Push the Limits of Visual SLAM

1 code implementation31 Mar 2020 Wenshan Wang, Delong Zhu, Xiangwei Wang, Yaoyu Hu, Yuheng Qiu, Chen Wang, Yafei Hu, Ashish Kapoor, Sebastian Scherer

We present a challenging dataset, the TartanAir, for robot navigation task and more.


Cooperative Pursuit with Multi-Pursuer and One Faster Free-moving Evader

1 code implementation IEEE Transactions on Cybernetics 2020 Xu Fang, Chen Wang, Lihua Xie, Jie Chen

When the faster evader is allowed to move freely without any constraint, the main issues are how to form an encirclement to trap the evader into the capture domain, how to balance between forming an encirclement and approaching the faster evader, and what conditions make the capture possible.

Systems and Control Systems and Control

Fully Dense Neural Network for the Automatic Modulation Recognition

no code implementations7 Dec 2019 Miao Du, Qin Yu, Shaomin Fei, Chen Wang, Xiao-Feng Gong, Ruisen Luo

Nowadays, we mainly use various convolution neural network (CNN) structures to extract features from radio data or spectrogram in AMR.

Kernel learning for visual perception

1 code implementation6 Dec 2019 Chen Wang

To this end, the novel kernel learning methods for several basic visual perceptual tasks, including object tracking, localization, mapping, and image recognition, are proposed and demonstrated both theoretically and practically.

Activity Recognition Loop Closure Detection +7

Transferable Force-Torque Dynamics Model for Peg-in-hole Task

no code implementations30 Nov 2019 Junfeng Ding, Chen Wang, Cewu Lu

We present a learning-based force-torque dynamics to achieve model-based control for contact-rich peg-in-hole task using force-only inputs.

Model-based Reinforcement Learning

SAG-VAE: End-to-end Joint Inference of Data Representations and Feature Relations

no code implementations27 Nov 2019 Chen Wang, Chengyuan Deng, Vladimir Ivanov

Variational Autoencoders (VAEs) are powerful in data representation inference, but it cannot learn relations between features with its vanilla form and common variations.

Image Reconstruction Relational Reasoning

Platoon trajectories generation: A unidirectional interconnected LSTM-based car following model

no code implementations25 Oct 2019 Yangxin Lin, Ping Wang, Yang Zhou, Fan Ding, Chen Wang, Huachun Tan

However, the traffic micro-simulation accuracy of car following models in a platoon level, especially during traffic oscillations, still needs to be enhanced.

Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

3 code implementations30 Sep 2019 Zinan Lin, Alankar Jain, Chen Wang, Giulia Fanti, Vyas Sekar

By shedding light on the promise and challenges, we hope our work can rekindle the conversation on workflows for data sharing.

Synthetic Data Generation Time Series

A Radio Signal Modulation Recognition Algorithm Based on Residual Networks and Attention Mechanisms

no code implementations27 Sep 2019 Ruisen Luo, Tao Hu, Zuodong Tang, Chen Wang, Xiaofeng Gong, Haiyan Tu

To solve the problem of inaccurate recognition of types of communication signal modulation, a RNN neural network recognition algorithm combining residual block network with attention mechanism is proposed.

Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification

no code implementations9 Aug 2019 Chen Wang, Chengyuan Deng, Zhoulu Yu, Dafeng Hui, Xiaofeng Gong, Ruisen Luo

In addition, the proposed method has other preferred properties such as special advantages in dealing with highly imbalanced data, and it pioneers the research on the regularization for dynamic ensemble methods.

General Classification

Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoost

1 code implementation5 Aug 2019 Chen Wang, Chengyuan Deng, Suzhen Wang

The paper presents Imbalance-XGBoost, a Python package that combines the powerful XGBoost software with weighted and focal losses to tackle binary label-imbalanced classification tasks.

Classification General Classification +1

Spearphone: A Speech Privacy Exploit via Accelerometer-Sensed Reverberations from Smartphone Loudspeakers

1 code implementation12 Jul 2019 S Abhishek Anand, Chen Wang, Jian Liu, Nitesh Saxena, Yingying Chen

In this paper, we build a speech privacy attack that exploits speech reverberations generated from a smartphone's inbuilt loudspeaker captured via a zero-permission motion sensor (accelerometer).

Cryptography and Security

Multi-layer Attention Mechanism for Speech Keyword Recognition

no code implementations10 Jul 2019 Ruisen Luo, Tianran Sun, Chen Wang, Miao Du, Zuodong Tang, Kai Zhou, Xiao-Feng Gong, Xiaomei Yang

The key idea is that, in addition to the conventional attention mechanism, information of layers prior to feature extraction and LSTM are introduced into attention weights calculations.

Ranked #4 on Keyword Spotting on Google Speech Commands (Google Speech Commands V2 20 metric)

Keyword Spotting Speech Recognition

Memetic EDA-Based Approaches to Comprehensive Quality-Aware Automated Semantic Web Service Composition

no code implementations19 Jun 2019 Chen Wang, Hui Ma, Gang Chen, Sven Hartmann

The objective of this problem is to find a solution with optimized or near-optimized overall QoS and QoSM within polynomial time over a service request.

Service Composition

Kervolutional Neural Networks

6 code implementations CVPR 2019 Chen Wang, Jianfei Yang, Lihua Xie, Junsong Yuan

Convolutional neural networks (CNNs) have enabled the state-of-the-art performance in many computer vision tasks.

Adversarial Examples on Graph Data: Deep Insights into Attack and Defense

2 code implementations5 Mar 2019 Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu

Based on this observation, we propose a defense approach which inspects the graph and recovers the potential adversarial perturbations.

Adversarial Attack Adversarial Defense

Evolutionary Multitasking for Semantic Web Service Composition

no code implementations18 Feb 2019 Chen Wang, Hui Ma, Gang Chen, Sven Hartmann

We also found that the use of the proper neighborhood structure can enhance the effectiveness of our approach.

Service Composition

Fast and Globally Optimal Rigid Registration of 3D Point Sets by Transformation Decomposition

no code implementations29 Dec 2018 Xuechen Li, Yinlong Liu, Yiru Wang, Chen Wang, Manning Wang, Zhijian Song

However, the existing global methods are slow for two main reasons: the computational complexity of BnB is exponential to the problem dimensionality (which is six for 3D rigid registration), and the bound evaluation used in BnB is inefficient.


Model-free Approach for Sensor Network Localization with Noisy Distance Measurement

1 code implementation18 Nov 2018 Xu Fang, Chen Wang, Thien-Minh Nguyen, Lihua Xie

In addition, different from the traditional filter-based localization methods which need kinetic model for localization, our proposed method is model-free and converts the localization problem to graph optimization problem.

Scalar Quantization as Sparse Least Square Optimization

no code implementations1 Mar 2018 Chen Wang, Xiaomei Yang, Shaomin Fei, Kai Zhou, Xiao-Feng Gong, Miao Du, Ruisen Luo

Furthermore, to compute quantization results with a given amount of values/clusters, this paper designed an iterative method and a clustering-based method, and both of them are built on sparse least square.


Graph Optimization Approach to Range-based Localization

1 code implementation28 Feb 2018 Xu Fang, Chen Wang, Thien-Minh Nguyen, Lihua Xie

In this paper, we propose a general graph optimization based framework for localization, which can accommodate different types of measurements with varying measurement time intervals.


Robust Propensity Score Computation Method based on Machine Learning with Label-corrupted Data

no code implementations9 Jan 2018 Chen Wang, Suzhen Wang, Fuyan Shi, Zaixiang Wang

The experimental results illustrate that xgboost propensity scores computing with the data processed by our method could outperform the same method with original data, and the advantages of our method increases as we add some artificial corruptions to the dataset.

Fine-grained Pattern Matching Over Streaming Time Series

no code implementations27 Oct 2017 Rong Kang, Chen Wang, Peng Wang, Yuting Ding, Jian-Min Wang

Hence, we formulate a new problem, called "fine-grained pattern matching", which allows users to specify varied granularities of matching deviation to different segments of a given pattern, and fuzzy regions for adaptive breakpoints determination between consecutive segments.

Time Series

Non-iterative RGB-D-inertial Odometry

1 code implementation16 Oct 2017 Chen Wang, Minh-Chung Hoang, Lihua Xie, Junsong Yuan

This paper presents a non-iterative solution to RGB-D-inertial odometry system.


Ultra-Wideband Aided Fast Localization and Mapping System

1 code implementation 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017 Chen Wang, Handuo Zhang, Thien-Minh Nguyen, Lihua Xie

This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera.


Kernel Cross-Correlator

2 code implementations12 Sep 2017 Chen Wang, Le Zhang, Lihua Xie, Junsong Yuan

Cross-correlator plays a significant role in many visual perception tasks, such as object detection and tracking.

Activity Recognition Object Detection +1

Interpreting Shared Deep Learning Models via Explicable Boundary Trees

no code implementations12 Sep 2017 Huijun Wu, Chen Wang, Jie Yin, Kai Lu, Liming Zhu

In this paper, we propose a method to disclose a small set of training data that is just sufficient for users to get the insight of a complicated model.

Decision Making

A discriminative view of MRF pre-processing algorithms

no code implementations ICCV 2017 Chen Wang, Charles Herrmann, Ramin Zabih

While Markov Random Fields (MRFs) are widely used in computer vision, they present a quite challenging inference problem.

Relaxation-Based Preprocessing Techniques for Markov Random Field Inference

no code implementations CVPR 2016 Chen Wang, Ramin Zabih

Markov Random Fields (MRFs) are a widely used graphical model, but the inference problem is NP-hard.

Improving Raw Image Storage Efficiency by Exploiting Similarity

no code implementations19 Apr 2016 Binqi Zhang, Chen Wang, Bing Bing Zhou, Albert Y. Zomaya

To improve the temporal and spatial storage efficiency, researchers have intensively studied various techniques, including compression and deduplication.

A Primal-Dual Algorithm for Higher-Order Multilabel Markov Random Fields

no code implementations CVPR 2014 Alexander Fix, Chen Wang, Ramin Zabih

Graph cuts method such as a-expansion [4] and fusion moves [22] have been successful at solving many optimization problems in computer vision.

14 Denoising

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