Search Results for author: Hong Wang

Found 33 papers, 14 papers with code

InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction

1 code implementation11 Sep 2021 Hong Wang, Yuexiang Li, Haimiao Zhang, Jiawei Chen, Kai Ma, Deyu Meng, Yefeng Zheng

For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT imaging geometry constraint is not fully embedded into the network during training, leaving room for further performance improvement; 2) the model interpretability is lack of sufficient consideration.

Metal Artifact Reduction

AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning

1 code implementation ICCV 2021 Hong Wang, Yuefan Deng, Shinjae Yoo, Haibin Ling, Yuewei Lin

The attention knowledge is obtained from a weight-fixed model trained on a clean dataset, referred to as a teacher model, and transferred to a model that is under training on adversarial examples (AEs), referred to as a student model.

Adversarial Attack Knowledge Distillation +1

RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining

1 code implementation14 Jul 2021 Hong Wang, Qi Xie, Qian Zhao, Yong Liang, Deyu Meng

To handle such an ill-posed single image deraining task, in this paper, we specifically build a novel deep architecture, called rain convolutional dictionary network (RCDNet), which embeds the intrinsic priors of rain streaks and has clear interpretability.

Single Image Deraining

Symmetric Reduction of Regular Controlled Lagrangian System with Momentum Map

no code implementations11 Mar 2021 Hong Wang

Then we give a good expression of the dynamical vector field of the RCL system, such that we can describe the RCL-equivalence for the RCL systems.

Symplectic Geometry Differential Geometry Dynamical Systems 53D20, 70H33, 70Q05

Decision-making for Autonomous Vehicles on Highway: Deep Reinforcement Learning with Continuous Action Horizon

no code implementations26 Aug 2020 Teng Liu, Hong Wang, Bing Lu, Jun Li, Dongpu Cao

Decision-making strategy for autonomous vehicles de-scribes a sequence of driving maneuvers to achieve a certain navigational mission.

Autonomous Vehicles Decision Making

From Rain Generation to Rain Removal

1 code implementation CVPR 2021 Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng, Deyu Meng

For the single image rain removal (SIRR) task, the performance of deep learning (DL)-based methods is mainly affected by the designed deraining models and training datasets.

Single Image Deraining Variational Inference

Digital Quadruplets for Cyber-Physical-Social Systems based Parallel Driving: From Concept to Applications

no code implementations21 Jul 2020 Teng Liu, Xing Yang, Hong Wang, Xiaolin Tang, Long Chen, Huilong Yu, Fei-Yue Wang

The three virtual vehicles (descriptive, predictive, and prescriptive) dynamically interact with the real one in order to enhance the safety and performance of the real vehicle.

Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition

no code implementations16 Jul 2020 Teng Liu, Xiaolin Tang, Jiaxin Chen, Hong Wang, Wenhao Tan, Yalian Yang

Energy management strategies (EMSs) are the most significant components in hybrid electric vehicles (HEVs) because they decide the potential of energy conservation and emission reduction.

Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study

no code implementations16 Jul 2020 Teng Liu, Xingyu Mu, Xiaolin Tang, Bing Huang, Hong Wang, Dongpu Cao

This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL).

Autonomous Vehicles Decision Making

Structural Residual Learning for Single Image Rain Removal

no code implementations19 May 2020 Hong Wang, Yichen Wu, Qi Xie, Qian Zhao, Yong Liang, Deyu Meng

Such a structural residual setting guarantees the rain layer extracted by the network finely comply with the prior knowledge of general rain streaks, and thus regulates sound rain shapes capable of being well extracted from rainy images in both training and predicting stages.

Rain Removal

A Model-driven Deep Neural Network for Single Image Rain Removal

1 code implementation CVPR 2020 Hong Wang, Qi Xie, Qian Zhao, Deyu Meng

Specifically, based on the convolutional dictionary learning mechanism for representing rain, we propose a novel single image deraining model and utilize the proximal gradient descent technique to design an iterative algorithm only containing simple operators for solving the model.

Dictionary Learning Single Image Deraining

Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework

no code implementations5 Feb 2020 Hongyu Li, Dan Meng, Hong Wang, Xiaolin Li

With strict protections and regulations of data privacy and security, conventional machine learning based on centralized datasets is confronted with significant challenges, making artificial intelligence (AI) impractical in many mission-critical and data-sensitive scenarios, such as finance, government, and health.

Federated Learning

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation

no code implementations NeurIPS 2019 Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep K. Ravikumar

We show that this algorithm has an approximation ratio of $O((k+1)^{1/p})$ for $1\le p\le 2$ and $O((k+1)^{1-1/p})$ for $p\ge 2$.

Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation

no code implementations30 Oct 2019 Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar

We show that this algorithm has an approximation ratio of $O((k+1)^{1/p})$ for $1\le p\le 2$ and $O((k+1)^{1-1/p})$ for $p\ge 2$.

Fine-tune Bert for DocRED with Two-step Process

1 code implementation26 Sep 2019 Hong Wang, Christfried Focke, Rob Sylvester, Nilesh Mishra, William Wang

Modelling relations between multiple entities has attracted increasing attention recently, and a new dataset called DocRED has been collected in order to accelerate the research on the document-level relation extraction.

Document-level Relation Extraction

A Survey on Rain Removal from Video and Single Image

1 code implementation18 Sep 2019 Hong Wang, Yichen Wu, Minghan Li, Qian Zhao, Deyu Meng

The investigations on rain removal from video or a single image has thus been attracting much research attention in the field of computer vision and pattern recognition, and various methods have been proposed against this task in the recent years.

Rain Removal

Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

no code implementations WS 2019 Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Hong Wang, Shiyu Chang, Murray Campbell, William Yang Wang

To resolve this issue, we introduce a new sub-problem of open-domain multi-hop QA, which aims to recognize the bridge (\emph{i. e.}, the anchor that links to the answer passage) from the context of a set of start passages with a reading comprehension model.

Information Retrieval Multi-hop Question Answering +2

TabFact: A Large-scale Dataset for Table-based Fact Verification

1 code implementation ICLR 2020 Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, William Yang Wang

To this end, we construct a large-scale dataset called TabFact with 16k Wikipedia tables as the evidence for 118k human-annotated natural language statements, which are labeled as either ENTAILED or REFUTED.

Fact Checking Fact Verification +3

Inverse Structural Design of Graphene/Boron Nitride Hybrids by Regressional GAN

1 code implementation21 Aug 2019 Yuan Dong, Dawei Li, Chi Zhang, Chuhan Wu, Hong Wang, Ming Xin, Jianlin Cheng, Jian Lin

A significant novelty of the proposed RGAN is that it combines the supervised and regressional convolutional neural network (CNN) with the traditional unsupervised GAN, thus overcoming the common technical barrier in the traditional GANs, which cannot generate data associated with given continuous quantitative labels.

Computational Physics Materials Science Applied Physics

Meta Reasoning over Knowledge Graphs

no code implementations13 Aug 2019 Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang

The ability to reason over learned knowledge is an innate ability for humans and humans can easily master new reasoning rules with only a few demonstrations.

Few-Shot Learning Knowledge Base Completion +1

TWEETQA: A Social Media Focused Question Answering Dataset

no code implementations ACL 2019 Wenhan Xiong, Jiawei Wu, Hong Wang, Vivek Kulkarni, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang

With social media becoming increasingly pop-ular on which lots of news and real-time eventsare reported, developing automated questionanswering systems is critical to the effective-ness of many applications that rely on real-time knowledge.

Question Answering

Improving Branch Prediction By Modeling Global History with Convolutional Neural Networks

no code implementations20 Jun 2019 Stephen J Tarsa, Chit-Kwan Lin, Gokce Keskin, Gautham Chinya, Hong Wang

CPU branch prediction has hit a wall--existing techniques achieve near-perfect accuracy on 99% of static branches, and yet the mispredictions that remain hide major performance gains.

Self-Supervised Learning for Contextualized Extractive Summarization

1 code implementation ACL 2019 Hong Wang, Xin Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang

Existing models for extractive summarization are usually trained from scratch with a cross-entropy loss, which does not explicitly capture the global context at the document level.

Document-level Extractive Summarization +1

Sentence Embedding Alignment for Lifelong Relation Extraction

2 code implementations NAACL 2019 Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang

We formulate such a challenging problem as lifelong relation extraction and investigate memory-efficient incremental learning methods without catastrophically forgetting knowledge learned from previous tasks.

Incremental Learning Relation Extraction +1

Adversarial Structured Prediction for Multivariate Measures

no code implementations20 Dec 2017 Hong Wang, Ashkan Rezaei, Brian D. Ziebart

Many predicted structured objects (e. g., sequences, matchings, trees) are evaluated using the F-score, alignment error rate (AER), or other multivariate performance measures.

Named Entity Recognition Structured Prediction +1

Arbitrary-Oriented Scene Text Detection via Rotation Proposals

4 code implementations3 Mar 2017 Jianqi Ma, Weiyuan Shao, Hao Ye, Li Wang, Hong Wang, Yingbin Zheng, xiangyang xue

This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images.

Region Proposal Scene Text +1

Adversarial Prediction Games for Multivariate Losses

no code implementations NeurIPS 2015 Hong Wang, Wei Xing, Kaiser Asif, Brian Ziebart

Multivariate loss functions are used to assess performance in many modern prediction tasks, including information retrieval and ranking applications.

Information Retrieval

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