Search Results for author: Chao Wang

Found 119 papers, 16 papers with code

Discriminative Partial Domain Adversarial Network

no code implementations ECCV 2020 Jian Hu, Hongya Tuo, Chao Wang, Lingfeng Qiao, Haowen Zhong, Junchi Yan, Zhongliang Jing, Henry Leung

Previous methods typically match the whole source domain to target domain, which causes negative transfer due to the source-negative classes in source domain that does not exist in target domain.

Partial Domain Adaptation Transfer Learning

Attacking and Defending Deep Reinforcement Learning Policies

no code implementations16 May 2022 Chao Wang

Recent studies have shown that deep reinforcement learning (DRL) policies are vulnerable to adversarial attacks, which raise concerns about applications of DRL to safety-critical systems.


Rethinking Reinforcement Learning based Logic Synthesis

no code implementations16 May 2022 Chao Wang, Chen Chen, Dong Li, Bin Wang

Recently, reinforcement learning has been used to address logic synthesis by formulating the operator sequence optimization problem as a Markov decision process.


Using Augmented Face Images to Improve Facial Recognition Tasks

no code implementations13 May 2022 Shuo Cheng, Guoxian Song, Wan-Chun Ma, Chao Wang, Linjie Luo

We present a framework that uses GAN-augmented images to complement certain specific attributes, usually underrepresented, for machine learning model training.

A Multi-Transformation Evolutionary Framework for Influence Maximization in Social Networks

no code implementations7 Apr 2022 Chao Wang, Jiaxuan Zhao, Lingling Li, Licheng Jiao, Jing Liu, Kai Wu

Influence maximization is a key issue for mining the deep information of social networks, which aims to select a seed set from the network to maximize the number of influenced nodes.

Federated Self-Supervised Learning for Acoustic Event Classification

no code implementations22 Mar 2022 Meng Feng, Chieh-Chi Kao, Qingming Tang, Ming Sun, Viktor Rozgic, Spyros Matsoukas, Chao Wang

Standard acoustic event classification (AEC) solutions require large-scale collection of data from client devices for model optimization.

Classification Continual Learning +2

A Principled Design of Image Representation: Towards Forensic Tasks

1 code implementation2 Mar 2022 Shuren Qi, Yushu Zhang, Chao Wang, Jiantao Zhou, Xiaochun Cao

Image forensics is a rising topic as the trustworthy multimedia content is critical for modern society.

Image Forensics

Rule Mining over Knowledge Graphs via Reinforcement Learning

no code implementations21 Feb 2022 Lihan Chen, Sihang Jiang, Jingping Liu, Chao Wang, Sheng Zhang, Chenhao Xie, Jiaqing Liang, Yanghua Xiao, Rui Song

Knowledge graphs (KGs) are an important source repository for a wide range of applications and rule mining from KGs recently attracts wide research interest in the KG-related research community.

Knowledge Graphs reinforcement-learning

A multi-domain VNE algorithm based on multi-objective optimization for IoD architecture in Industry 4.0

no code implementations8 Feb 2022 Peiying Zhang, Chao Wang, Zeyu Qin, Haotong Cao

Network virtualization technology is a promising technology to support IoD, so the allocation of virtual resources becomes a crucial issue in IoD.

Network Embedding

Network Resource Allocation Strategy Based on Deep Reinforcement Learning

no code implementations3 Feb 2022 Shidong Zhang, Chao Wang, Junsan Zhang, Youxiang Duan, Xinhong You, Peiying Zhang

This paper proposes a two-stage VNE algorithm based on deep reinforcement learning (DRL) (TS-DRL-VNE) for the problem that the mapping result of existing heuristic algorithm is easy to converge to the local optimal solution.

Network Embedding reinforcement-learning

Space-Air-Ground Integrated Multi-domain Network Resource Orchestration based on Virtual Network Architecture: a DRL Method

no code implementations3 Feb 2022 Peiying Zhang, Chao Wang, Neeraj Kumar, Lei Liu

Based on virtual network architecture and deep reinforcement learning (DRL), we model SAGIN's heterogeneous resource orchestration as a multi-domain virtual network embedding (VNE) problem, and propose a SAGIN cross-domain VNE algorithm.

Network Embedding

Security-Aware Virtual Network Embedding Algorithm based on Reinforcement Learning

no code implementations3 Feb 2022 Peiying Zhang, Chao Wang, Chunxiao Jiang, Abderrahim Benslimane

In addition, as the use of intelligent learning algorithm to solve the problem of VNE has become a trend, this method is gradually outdated.

Network Embedding reinforcement-learning

Multi Objective Resource Optimization of Wireless Network Based on Cross Domain Virtual Network Embedding

no code implementations3 Feb 2022 Chao Wang, Tao Dong, Youxiang Duan, Qifeng Sun, Peiying Zhang

Resource allocation in virtual network is essentially a problem of allocating underlying resources for virtual network requests (VNRs).

Network Embedding

Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm

no code implementations3 Feb 2022 Peiying Zhang, Chao Wang, Chunxiao Jiang, Neeraj Kumar, Qinghua Lu

Based on the above two problems faced by ICPSs, we propose a virtual network embedded (VNE) algorithm with computing, storage resources and security constraints to ensure the rationality and security of resource allocation in ICPSs.

Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT

no code implementations3 Feb 2022 Peiying Zhang, Chao Wang, Chunxiao Jiang, Zhu Han

Therefore, we propose a FL algorithm assisted by DRL, which can take into account the privacy and efficiency of data training of IIoT equipment.

Federated Learning reinforcement-learning +1

LinSyn: Synthesizing Tight Linear Bounds for Arbitrary Neural Network Activation Functions

no code implementations31 Jan 2022 Brandon Paulsen, Chao Wang

The most scalable approaches to certifying neural network robustness depend on computing sound linear lower and upper bounds for the network's activation functions.

Sentiment-Aware Automatic Speech Recognition pre-training for enhanced Speech Emotion Recognition

no code implementations27 Jan 2022 Ayoub Ghriss, Bo Yang, Viktor Rozgic, Elizabeth Shriberg, Chao Wang

We pre-train SER model simultaneously on Automatic Speech Recognition (ASR) and sentiment classification tasks to make the acoustic ASR model more ``emotion aware''.

Automatic Speech Recognition Classification +2

MOORe: Model-based Offline-to-Online Reinforcement Learning

no code implementations25 Jan 2022 Yihuan Mao, Chao Wang, Bin Wang, Chongjie Zhang

With the success of offline reinforcement learning (RL), offline trained RL policies have the potential to be further improved when deployed online.


Opinion Dynamics in Financial Markets via Random Networks

no code implementations14 Jan 2022 Mateus F. B. Granha, André L. M. Vilela, Chao Wang, Kenric P. Nelson, H. Eugene Stanley

We investigate the financial market dynamics by introducing a heterogeneous agent-based opinion formation model.

Evolutionary Multitasking AUC Optimization

1 code implementation4 Jan 2022 Chao Wang, Kai Wu, Jing Liu

Inspired by the characteristic of pairwise learning, the cheap AUC optimization task with a small-scale dataset sampled from the large-scale dataset is constructed to promote the AUC accuracy of the original, large-scale, and expensive AUC optimization task.

What Knowledge can be Transferred Between Network Reconstruction and Community Detection?

no code implementations4 Jan 2022 Kai Wu, Chao Wang, Junyuan Chen, Jing Liu

Inspired by the fact that a more precise network structure may promote the accuracy of community discovery and the better communities may promote the performance of network reconstruction (NR), this paper develops an evolutionary multitasking framework to make full use of explicit shareable knowledge among these two tasks to improve their performance; we refer to this framework as EMTNRCD.

Community Detection Transfer Learning

DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training

no code implementations31 Dec 2021 Xianglin Yang, Yun Lin, Ruofan Liu, Zhenfeng He, Chao Wang, Jin Song Dong, Hong Mei

Moreover, our case study shows that our visual solution can well reflect the characteristics of various training scenarios, showing good potential of DVI as a debugging tool for analyzing deep learning training processes.

Active Learning

Topic Modeling Revisited: A Document Graph-based Neural Network Perspective

1 code implementation NeurIPS 2021 Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, HengShu Zhu, Hui Xiong

To this end, in this paper, we revisit the task of topic modeling by transforming each document into a directed graph with word dependency as edges between word nodes, and develop a novel approach, namely Graph Neural Topic Model (GNTM).

Variational Inference

Portfolio optimization with idiosyncratic and systemic risks for financial networks

no code implementations22 Nov 2021 Yajie Yang, Longfeng Zhao, Lin Chen, Chao Wang, Jihui Han

The two risks are measured by the idiosyncratic variance and the network clustering coefficient derived from the asset correlation networks, respectively.

Portfolio Optimization

SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

no code implementations17 Nov 2021 Hangyu Mao, Chao Wang, Xiaotian Hao, Yihuan Mao, Yiming Lu, Chengjie WU, Jianye Hao, Dong Li, Pingzhong Tang

The MineRL competition is designed for the development of reinforcement learning and imitation learning algorithms that can efficiently leverage human demonstrations to drastically reduce the number of environment interactions needed to solve the complex \emph{ObtainDiamond} task with sparse rewards.

Imitation Learning reinforcement-learning

Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness

1 code implementation24 Oct 2021 Dazhong Shen, Chuan Qin, Chao Wang, HengShu Zhu, Enhong Chen, Hui Xiong

As one of the most popular generative models, Variational Autoencoder (VAE) approximates the posterior of latent variables based on amortized variational inference.

Variational Inference

Learning a self-supervised tone mapping operator via feature contrast masking loss

no code implementations19 Oct 2021 Chao Wang, Bin Chen, Hans-Peter Seidel, Karol Myszkowski, Ana Serrano

High Dynamic Range (HDR) content is becoming ubiquitous due to the rapid development of capture technologies.

Tone Mapping

Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs

no code implementations15 Oct 2021 Ryan Jacobs, Mingren Shen, YuHan Liu, Wei Hao, Xiaoshan Li, Ruoyu He, Jacob RC Greaves, Donglin Wang, Zeming Xie, Zitong Huang, Chao Wang, Kevin G. Field, Dane Morgan

In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional Neural Network (Mask R-CNN) model.

Object Detection Semantic Segmentation

Towards High-fidelity Singing Voice Conversion with Acoustic Reference and Contrastive Predictive Coding

no code implementations10 Oct 2021 Chao Wang, Zhonghao Li, Benlai Tang, Xiang Yin, Yuan Wan, Yibiao Yu, Zejun Ma

Experiments show that, compared with the baseline models, our proposed model can significantly improve the naturalness of converted singing voices and the similarity with the target singer.

Automatic Speech Recognition Voice Conversion

Self-Adaptive Partial Domain Adaptation

no code implementations18 Sep 2021 Jian Hu, Hongya Tuo, Shizhao Zhang, Chao Wang, Haowen Zhong, Zhikang Zou, Zhongliang Jing, Henry Leung, Ruping Zou

Partial Domain adaptation (PDA) aims to solve a more practical cross-domain learning problem that assumes target label space is a subset of source label space.

Partial Domain Adaptation

A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting

no code implementations1 Jun 2021 Chao Wang, Richard Gerlach

The usefulness of the proposed measurement equation in a Realized-GARCH model has been evaluated via a comprehensive empirical study, by forecasting the 1% and 2. 5% Value-at-Risk and Expected Shortfall on six market indices.

Explainability via Interactivity? Supporting Nonexperts' Sensemaking of Pretrained CNN by Interacting with Their Daily Surroundings

no code implementations31 May 2021 Chao Wang, Pengcheng An

Current research on Explainable AI (XAI) heavily targets on expert users (data scientists or AI developers).

TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

1 code implementation ACL 2021 Fengbin Zhu, Wenqiang Lei, Youcheng Huang, Chao Wang, Shuo Zhang, Jiancheng Lv, Fuli Feng, Tat-Seng Chua

In this work, we extract samples from real financial reports to build a new large-scale QA dataset containing both Tabular And Textual data, named TAT-QA, where numerical reasoning is usually required to infer the answer, such as addition, subtraction, multiplication, division, counting, comparison/sorting, and the compositions.

Question Answering

Convolutions for Spatial Interaction Modeling

no code implementations15 Apr 2021 Zhaoen Su, Chao Wang, David Bradley, Carlos Vallespi-Gonzalez, Carl Wellington, Nemanja Djuric

In many different fields interactions between objects play a critical role in determining their behavior.

Autonomous Vehicles

Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach

no code implementations11 Apr 2021 Giuseppe Storti, Chao Wang

A novel forecast combination and weighted quantile based tail-risk forecasting framework is proposed, aiming to reduce the impact of modelling uncertainty in tail-risk forecasting.

An Emotion-controlled Dialog Response Generation Model with Dynamic Vocabulary

no code implementations4 Mar 2021 Shuangyong Song, Kexin Wang, Chao Wang, Haiqing Chen, Huan Chen

In response generation task, proper sentimental expressions can obviously improve the human-like level of the responses.

Response Generation

High $J_{\rm c}$ and low anisotropy of hydrogen doped NdFeAsO superconducting thin film

no code implementations26 Feb 2021 Kazumasa Iida, Jens Hänisch, Keisuke Kondo, Mingyu Chen, Takafumi Hatano, Chao Wang, Hikaru Saito, Satoshi Hata, Hiroshi Ikuta

The anisotropic Ginzburg-Landau scaling for the angle dependence of $J_{\rm c}$ yielded temperature-dependent scaling parameters $\gamma_{\rm J}$ that decreased from 1. 6 at 30 K to 1. 3 at 5 K. This is opposite to the behaviour of NdFeAs(O, F).


The impact of $a_0^0(980)-f_0(980)$ mixing on the localized $CP$ violations of the $B^-\rightarrow K^- π^+π^-$ decay

no code implementations4 Feb 2021 Jing-Juan Qi, Zhen-Yang Wang, Chao Wang, Zhen-Hua Zhang, Xin-Heng Guo

In the framework of the QCD factorization approach, we study the localized $CP$ violations of the $B^-\rightarrow K^- \pi^+\pi^-$ decay with and without $a_0^0(980)-f_0(980)$ mixing mechanism, respectively, and find that the localized $CP$ violation can be enhanced by this mixing effect when the mass of the $\pi^+\pi^-$ pair is in the vicinity of the $f_0(980)$ resonance.

High Energy Physics - Phenomenology

Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering

no code implementations4 Jan 2021 Fengbin Zhu, Wenqiang Lei, Chao Wang, Jianming Zheng, Soujanya Poria, Tat-Seng Chua

Open-domain Question Answering (OpenQA) is an important task in Natural Language Processing (NLP), which aims to answer a question in the form of natural language based on large-scale unstructured documents.

Machine Reading Comprehension Open-Domain Question Answering

Minimizing L1 over L2 norms on the gradient

no code implementations4 Jan 2021 Chao Wang, Min Tao, Chen-Nee Chuah, James Nagy, Yifei Lou

Consequently, we postulate that applying L1/L2 on the gradient is better than the classic total variation (the L1 norm on the gradient) to enforce the sparsity of the image gradient.

Intragroup sparsity for efficient inference

no code implementations1 Jan 2021 Zilin Yu, Chao Wang, Xin Wang, Yong Zhao, Xundong Wu

This work studies intragroup sparsity, a fine-grained structural constraint on network weight parameters.

Realization of epitaxial thin films of the superconductor K-doped BaFe$_\text{2}$As$_\text{2}$

no code implementations26 Dec 2020 Dongyi Qin, Kazumasa Iida, Takafumi Hatano, Hikaru Saito, Yiming Ma, Chao Wang, Satoshi Hata, Michio Naito, Akiyasu Yamamoto

The iron-based superconductor Ba$_{1-x}$K$_x$Fe$_\text{2}$As$_\text{2}$ is emerging as a key material for high magnetic field applications owing to the recent developments in superconducting wires and bulk permanent magnets.


A comprehensive study on the semileptonic decay of heavy flavor mesons

no code implementations8 Dec 2020 Lu Zhang, Xian-Wei Kang, Xin-Heng Guo, Ling-Yun Dai, Tao Luo, Chao Wang

The semileptonic decay of heavy flavor mesons offers a clean environment for extraction of the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements, which describes the CP-violating and flavor changing process in the Standard Model.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling

no code implementations COLING 2020 Xu Cao, Deyi Xiong, Chongyang Shi, Chao Wang, Yao Meng, Changjian Hu

Joint intent detection and slot filling has recently achieved tremendous success in advancing the performance of utterance understanding.

Intent Detection Slot Filling

Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization

no code implementations1 Nov 2020 Zhaoen Su, Chao Wang, Henggang Cui, Nemanja Djuric, Carlos Vallespi-Gonzalez, David Bradley

To address this issue we propose a simple and general representation for temporally continuous probabilistic trajectory prediction that is based on polynomial trajectory parameterization.

motion prediction Trajectory Prediction

NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation

no code implementations21 Sep 2020 Brandon Paulsen, Jingbo Wang, Jiawei Wang, Chao Wang

Unfortunately, existing methods either focus on verifying a single network or rely on loose approximations to prove the equivalence of two networks.

Tail risk forecasting using Bayesian realized EGARCH models

no code implementations12 Aug 2020 Vica Tendenan, Richard Gerlach, Chao Wang

Rigorous tail risk forecast evaluations show that the realized EGARCH models employing the standardized skewed Student-t distribution and incorporating sub-sampled realized range are favored, compared to a range of models.

Deep Learning Based Equalizer for MIMO-OFDM Systems with Insufficient Cyclic Prefix

no code implementations23 Jul 2020 Yan Sun, Chao Wang, Huan Cai, Chunming Zhao, Yiqun Wu, Yan Chen

In this paper, we study the equalization design for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with insufficient cyclic prefix (CP).

DiffRNN: Differential Verification of Recurrent Neural Networks

no code implementations20 Jul 2020 Sara Mohammadinejad, Brandon Paulsen, Chao Wang, Jyotirmoy V. Deshmukh

As the memory footprint and energy consumption of such components become a bottleneck, there is interest in compressing and optimizing such networks using a range of heuristic techniques.

Speech Recognition

Limited-angle CT reconstruction via the L1/L2 minimization

no code implementations31 May 2020 Chao Wang, Min Tao, James Nagy, Yifei Lou

In this paper, we consider minimizing the L1/L2 term on the gradient for a limited-angle scanning problem in computed tomography (CT) reconstruction.

Computed Tomography (CT)

An Artificial-intelligence/Statistics Solution to Quantify Material Distortion for Thermal Compensation in Additive Manufacturing

no code implementations14 May 2020 Chao Wang, Shaofan Li, Danielle Zeng, Xinhai Zhu

In this paper, we introduce a probabilistic statistics solution or artificial intelligence (AI) approach to identify and quantify permanent (non-zero strain) continuum/material deformation only based on the scanned material data in the spatial configuration and the shape of the initial design configuration or the material configuration.

Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles

no code implementations11 May 2020 Giuseppe Storti, Chao Wang

The proposed models are applied to 7 stock market indices and their forecasting performances are compared to those of a range of parametric, non-parametric and semi-parametric models, including GARCH, Conditional AutoRegressive Expectile (CARE), joint VaR and ES quantile regression models and simple average of quantiles.

Time Series

LSHR-Net: a hardware-friendly solution for high-resolution computational imaging using a mixed-weights neural network

1 code implementation27 Apr 2020 Fangliang Bai, Jinchao Liu, Xiaojuan Liu, Margarita Osadchy, Chao Wang, Stuart J. Gibson

However, to date, there have been two major drawbacks: (1) the high-precision real-valued sensing patterns proposed in the majority of existing works can prove problematic when used with computational imaging hardware such as a digital micromirror sampling device and (2) the network structures for image reconstruction involve intensive computation, which is also not suitable for hardware deployment.

Image Reconstruction

Improving Recommendation Diversity by Highlighting the ExTrA Fabricated Experts

no code implementations24 Apr 2020 Ya-Hui An, Qiang Dong, Quan Yuan, Chao Wang

Nowadays, recommender systems (RSes) are becoming increasingly important to individual users and business marketing, especially in the online e-commerce scenarios.

Recommendation Systems

TCNN: Triple Convolutional Neural Network Models for Retrieval-based Question Answering System in E-commerce

no code implementations23 Apr 2020 Shuangyong Song, Chao Wang

Automatic question-answering (QA) systems have boomed during last few years, and commonly used techniques can be roughly categorized into Information Retrieval (IR)-based and generation-based.

Information Retrieval Question Answering +1

MLR: A Two-stage Conversational Query Rewriting Model with Multi-task Learning

no code implementations13 Apr 2020 Shuangyong Song, Chao Wang, Qianqian Xie, Xinxing Zu, Huan Chen, Haiqing Chen

In this paper, we propose the conversational query rewriting model - MLR, which is a Multi-task model on sequence Labeling and query Rewriting.

Multi-Task Learning

Suphx: Mastering Mahjong with Deep Reinforcement Learning

no code implementations30 Mar 2020 Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon

Artificial Intelligence (AI) has achieved great success in many domains, and game AI is widely regarded as its beachhead since the dawn of AI.


Adversarial Multimodal Representation Learning for Click-Through Rate Prediction

no code implementations7 Mar 2020 Xiang Li, Chao Wang, Jiwei Tan, Xiaoyi Zeng, Dan Ou, Bo Zheng

Finally, we achieve the multimodal item representations by combining both modality-specific and modality-invariant representations.

Click-Through Rate Prediction Representation Learning

Novelty-Prepared Few-Shot Classification

1 code implementation1 Mar 2020 Chao Wang, Ruo-Ze Liu, Han-Jia Ye, Yang Yu

We disclose that a classically fully trained feature extractor can leave little embedding space for unseen classes, which keeps the model from well-fitting the new classes.

Classification General Classification

SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback

1 code implementation23 Feb 2020 Chao Wang, HengShu Zhu, Chen Zhu, Chuan Qin, Hui Xiong

The recent development of online recommender systems has a focus on collaborative ranking from implicit feedback, such as user clicks and purchases.

Collaborative Ranking Recommendation Systems

Designing Interaction for Multi-agent Cooperative System in an Office Environment

no code implementations15 Feb 2020 Chao Wang, Stephan Hasler, Manuel Muehlig, Frank Joublin, Antonello Ceravola, Joerg Deigmoeller, Lydia Fischer

Future intelligent system will involve very various types of artificial agents, such as mobile robots, smart home infrastructure or personal devices, which share data and collaborate with each other to execute certain tasks. Designing an efficient human-machine interface, which can support users to express needs to the system, supervise the collaboration progress of different entities and evaluate the result, will be challengeable.

Semi-supervised ASR by End-to-end Self-training

no code implementations24 Jan 2020 Yang Chen, Weiran Wang, Chao Wang

While deep learning based end-to-end automatic speech recognition (ASR) systems have greatly simplified modeling pipelines, they suffer from the data sparsity issue.

Automatic Speech Recognition Data Augmentation

Data Techniques For Online End-to-end Speech Recognition

no code implementations24 Jan 2020 Yang Chen, Weiran Wang, I-Fan Chen, Chao Wang

Practitioners often need to build ASR systems for new use cases in a short amount of time, given limited in-domain data.

Data Augmentation Domain Adaptation +2

A Study of the Tasks and Models in Machine Reading Comprehension

no code implementations23 Jan 2020 Chao Wang

To provide a survey on the existing tasks and models in Machine Reading Comprehension (MRC), this report reviews: 1) the dataset collection and performance evaluation of some representative simple-reasoning and complex-reasoning MRC tasks; 2) the architecture designs, attention mechanisms, and performance-boosting approaches for developing neural-network-based MRC models; 3) some recently proposed transfer learning approaches to incorporating text-style knowledge contained in external corpora into the neural networks of MRC models; 4) some recently proposed knowledge base encoding approaches to incorporating graph-style knowledge contained in external knowledge bases into the neural networks of MRC models.

Machine Reading Comprehension Transfer Learning

A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting

no code implementations23 Jan 2020 Zhengkun Li, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Junbin Gao

Value-at-Risk (VaR) and Expected Shortfall (ES) are widely used in the financial sector to measure the market risk and manage the extreme market movement.

Bayesian Inference Time Series

NEW: A Generic Learning Model for Tie Strength Prediction in Networks

no code implementations15 Jan 2020 Zhen Liu, Hu Li, Chao Wang

Tie strength prediction, sometimes named weight prediction, is vital in exploring the diversity of connectivity pattern emerged in networks.

ReluDiff: Differential Verification of Deep Neural Networks

no code implementations10 Jan 2020 Brandon Paulsen, Jingbo Wang, Chao Wang

Existing verification techniques such as Reluplex, ReluVal, and DeepPoly provide formal guarantees, but they are designed for analyzing a single network instead of the relationship between two networks.

Attention Deep Model with Multi-Scale Deep Supervision for Person Re-Identification

no code implementations23 Nov 2019 Di Wu, Chao Wang, Yong Wu, De-Shuang Huang

Besides, most of the multi-scale models embedding the multi-scale feature learning block into the feature extraction deep network, which reduces the efficiency of inference network.

Person Re-Identification

Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network

no code implementations8 Nov 2019 Zhensong Wei, Chao Wang, Peng Hao, Matthew Barth

Accurate lane localization and lane change detection are crucial in advanced driver assistance systems and autonomous driving systems for safer and more efficient trajectory planning.

Autonomous Driving Change Detection +2

Data-Driven Multi-step Demand Prediction for Ride-hailing Services Using Convolutional Neural Network

no code implementations8 Nov 2019 Chao Wang, Yi Hou, Matthew Barth

In this study, a convolutional neural network (CNN)-based deep learning model is proposed for multi-step ride-hailing demand prediction using the trip request data in Chengdu, China, offered by DiDi Chuxing.

Autonomous Vehicles

Cross-Channel Intragroup Sparsity Neural Network

no code implementations26 Oct 2019 Zhilin Yu, Chao Wang, Xin Wang, Qing Wu, Yong Zhao, Xundong Wu

Modern deep neural networks rely on overparameterization to achieve state-of-the-art generalization.

Model Compression Network Pruning

PolSAR Image Classification Based on Dilated Convolution and Pixel-Refining Parallel Mapping network in the Complex Domain

1 code implementation24 Sep 2019 Dongling Xiao, Chang Liu, Qi. Wang, Chao Wang, Xin Zhang

For general supervised deep learning classification algorithms, the pixel-by-pixel algorithm achieves precise yet inefficient classification with a small number of labeled pixels, whereas the pixel mapping algorithm achieves efficient yet edge-rough classification with more prior labels required.

Classification General Classification +1

Acoustic scene analysis with multi-head attention networks

1 code implementation16 Sep 2019 Weimin Wang, Weiran Wang, Ming Sun, Chao Wang

Acoustic Scene Classification (ASC) is a challenging task, as a single scene may involve multiple events that contain complex sound patterns.

Acoustic Scene Classification General Classification +1

Improving Back-Translation with Uncertainty-based Confidence Estimation

1 code implementation IJCNLP 2019 Shuo Wang, Yang Liu, Chao Wang, Huanbo Luan, Maosong Sun

While back-translation is simple and effective in exploiting abundant monolingual corpora to improve low-resource neural machine translation (NMT), the synthetic bilingual corpora generated by NMT models trained on limited authentic bilingual data are inevitably noisy.

Low-Resource Neural Machine Translation Translation

Compression of Acoustic Event Detection Models With Quantized Distillation

no code implementations1 Jul 2019 Bowen Shi, Ming Sun, Chieh-Chi Kao, Viktor Rozgic, Spyros Matsoukas, Chao Wang

Acoustic Event Detection (AED), aiming at detecting categories of events based on audio signals, has found application in many intelligent systems.

Event Detection Knowledge Distillation +1

Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective

2 code implementations25 Jun 2019 Chengqiang Lu, Qi Liu, Chao Wang, Zhenya Huang, Peize Lin, Lixin He

In this paper, we propose a generalizable and transferable Multilevel Graph Convolutional neural Network (MGCN) for molecular property prediction.

Graph Regression Molecular Property Prediction

Multimodal and Multi-view Models for Emotion Recognition

no code implementations ACL 2019 Gustavo Aguilar, Viktor Rozgić, Weiran Wang, Chao Wang

Studies on emotion recognition (ER) show that combining lexical and acoustic information results in more robust and accurate models.

Emotion Recognition Frame +1

Joint 3D Localization and Classification of Space Debris using a Multispectral Rotating Point Spread Function

no code implementations11 Jun 2019 Chao Wang, Grey Ballard, Robert Plemmons, Sudhakar Prasad

We consider the problem of joint three-dimensional (3D) localization and material classification of unresolved space debris using a multispectral rotating point spread function (RPSF).

Classification General Classification +1

Efficient Plane-Based Optimization of Geometry and Texture for Indoor RGB-D Reconstruction

1 code implementation21 May 2019 Chao Wang, Xiaohu Guo

We propose a novel approach to reconstruct RGB-D indoor scene based on plane primitives.

Compression of Acoustic Event Detection Models with Low-rank Matrix Factorization and Quantization Training

no code implementations NIPS Workshop CDNNRIA 2018 Bowen Shi, Ming Sun, Chieh-Chi Kao, Viktor Rozgic, Spyros Matsoukas, Chao Wang

In this paper, we present a compression approach based on the combination of low-rank matrix factorization and quantization training, to reduce complexity for neural network based acoustic event detection (AED) models.

Event Detection Quantization

Versatile security analysis of measurement-device-independent quantum key distribution

no code implementations7 Jan 2019 Ignatius William Primaatmaja, Emilien Lavie, Koon Tong Goh, Chao Wang, Charles Ci Wen Lim

Interestingly, we also find that phase-matching QKD using only two coherent test states is enough to overcome the fundamental rate-distance limit of QKD.

Quantum Physics

A Survey of FPGA Based Deep Learning Accelerators: Challenges and Opportunities

no code implementations25 Dec 2018 Teng Wang, Chao Wang, Xuehai Zhou, Huaping Chen

With the rapid development of in-depth learning, neural network and deep learning algorithms have been widely used in various fields, e. g., image, video and voice processing.

A Scale Invariant Approach for Sparse Signal Recovery

no code implementations20 Dec 2018 Yaghoub Rahimi, Chao Wang, Hongbo Dong, Yifei Lou

In this paper, we study the ratio of the $L_1 $ and $L_2 $ norms, denoted as $L_1/L_2$, to promote sparsity.

MRI Reconstruction

Novel Sparse Recovery Algorithms for 3D Debris Localization using Rotating Point Spread Function Imagery

no code implementations27 Sep 2018 Chao Wang, Robert Plemmons, Sudhakar Prasad, Raymond Chan, Mila Nikolova

An optical imager that exploits off-center image rotation to encode both the lateral and depth coordinates of point sources in a single snapshot can perform 3D localization and tracking of space debris.

Explicit Utilization of General Knowledge in Machine Reading Comprehension

no code implementations ACL 2019 Chao Wang, Hui Jiang

To bridge the gap between Machine Reading Comprehension (MRC) models and human beings, which is mainly reflected in the hunger for data and the robustness to noise, in this paper, we explore how to integrate the neural networks of MRC models with the general knowledge of human beings.

Machine Reading Comprehension Question Answering

The Lower The Simpler: Simplifying Hierarchical Recurrent Models

no code implementations NAACL 2019 Chao Wang, Hui Jiang

To improve the training efficiency of hierarchical recurrent models without compromising their performance, we propose a strategy named as `the lower the simpler', which is to simplify the baseline models by making the lower layers simpler than the upper layers.

Coded Illumination and Imaging for Fluorescence Based Classification

no code implementations ECCV 2018 Yuta Asano, Misaki Meguro, Chao Wang, Antony Lam, Yinqiang Zheng, Takahiro Okabe, Imari Sato

The quick detection of specific substances in objects such as produce items via non-destructive visual cues is vital to ensuring the quality and safety of consumer products.

Classification General Classification +1

A Semi-parametric Realized Joint Value-at-Risk and Expected Shortfall Regression Framework

no code implementations5 Jul 2018 Chao Wang, Richard Gerlach, Qian Chen

One-day-ahead VaR and ES forecasting results favor the proposed models, especially when incorporating the sub-sampled Realized Variance and the sub-sampled Realized Range in the model.

Instance Map based Image Synthesis with a Denoising Generative Adversarial Network

no code implementations10 Jan 2018 Ziqiang Zheng, Chao Wang, Zhibin Yu, Haiyong Zheng, Bing Zheng

Semantic layouts based Image synthesizing, which has benefited from the success of Generative Adversarial Network (GAN), has drawn much attention in these days.

Denoising Image Generation

Close Yet Distinctive Domain Adaptation

no code implementations13 Apr 2017 Lingkun Luo, Xiaofang Wang, Shiqiang Hu, Chao Wang, Yu-Xing Tang, Liming Chen

Most previous research tackle this problem in seeking a shared feature representation between source and target domains while reducing the mismatch of their data distributions.

Domain Adaptation Image Classification +1

Quasi-homography warps in image stitching

no code implementations27 Jan 2017 Nan Li, Yifang Xu, Chao Wang

The naturalness of warps is gaining extensive attentions in image stitching.

Image Stitching

Perception-based energy functions in seam-cutting

no code implementations22 Jan 2017 Nan Li, Tianli Liao, Chao Wang

In this paper, we propose a novel perception-based energy function in the seam-cutting framework, which considers the nonlinearity and the nonuniformity of human perception in energy minimization.

Image Stitching

CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis

no code implementations20 Jun 2016 Maohua Zhu, Liu Liu, Chao Wang, Yuan Xie

To improve the performance and maintain the scalability, we present CNNLab, a novel deep learning framework using GPU and FPGA-based accelerators.

DLAU: A Scalable Deep Learning Accelerator Unit on FPGA

no code implementations23 May 2016 Chao Wang, Qi Yu, Lei Gong, Xi Li, Yuan Xie, Xuehai Zhou

As the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems.

A novel and automatic pectoral muscle identification algorithm for mediolateral oblique (MLO) view mammograms using ImageJ

no code implementations3 Mar 2016 Chao Wang

Pectoral muscle identification is often required for breast cancer risk analysis, such as estimating breast density.

Compositional Model based Fisher Vector Coding for Image Classification

1 code implementation16 Jan 2016 Lingqiao Liu, Peng Wang, Chunhua Shen, Lei Wang, Anton Van Den Hengel, Chao Wang, Heng Tao Shen

To handle this limitation, in this paper we break the convention which assumes that a local feature is drawn from one of few Gaussian distributions.

Classification General Classification +1

Multi-Agent Continuous Transportation with Online Balanced Partitioning

no code implementations23 Nov 2015 Chao Wang, Somchaya Liemhetcharat, Kian Hsiang Low

A continuous transportation task is one in which a multi-agent team visits a number of fixed locations, picks up objects, and delivers them to a final destination.

Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors

no code implementations NeurIPS 2014 Lingqiao Liu, Chunhua Shen, Lei Wang, Anton Van Den Hengel, Chao Wang

By calculating the gradient vector of the proposed model, we derive a new fisher vector encoding strategy, termed Sparse Coding based Fisher Vector Coding (SCFVC).

Fine-Grained Image Classification General Classification +1

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