Search Results for author: Yang Zhao

Found 71 papers, 20 papers with code

A Flexible Recurrent Residual Pyramid Network for Video Frame Interpolation

no code implementations ECCV 2020 Haoxian Zhang, Yang Zhao, Ronggang Wang

Inspired by classical pyramid energy minimization optical flow algorithms, this paper proposes a recurrent residual pyramid network (RRPN) for video frame interpolation.

Optical Flow Estimation Video Frame Interpolation

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency

no code implementations11 Sep 2021 Yonggan Fu, Yang Zhao, Qixuan Yu, Chaojian Li, Yingyan Lin

The recent breakthroughs of deep neural networks (DNNs) and the advent of billions of Internet of Things (IoT) devices have excited an explosive demand for intelligent IoT devices equipped with domain-specific DNN accelerators.

Quantization

EAR-NET: Error Attention Refining Network For Retinal Vessel Segmentation

no code implementations3 Jul 2021 Jun Wang, Yang Zhao, Linglong Qian, Xiaohan Yu, Yongsheng Gao

The precise detection of blood vessels in retinal images is crucial to the early diagnosis of the retinal vascular diseases, e. g., diabetic, hypertensive and solar retinopathies.

Retinal Vessel Segmentation

Cascaded Prediction Network via Segment Tree for Temporal Video Grounding

no code implementations CVPR 2021 Yang Zhao, Zhou Zhao, Zhu Zhang, Zhijie Lin

Temporal video grounding aims to localize the target segment which is semantically aligned with the given sentence in an untrimmed video.

Multi-Scale Context Aggregation Network with Attention-Guided for Crowd Counting

1 code implementation6 Apr 2021 Xin Wang, Yang Zhao, Tangwen Yang, Qiuqi Ruan

In this paper, we propose a multi-scale context aggregation network (MSCANet) based on single-column encoder-decoder architecture for crowd counting, which consists of an encoder based on a dense context-aware module (DCAM) and a hierarchical attention-guided decoder.

Crowd Counting

Analyzing and Quantifying Generalization in Convolutional Neural Networks

no code implementations2 Apr 2021 Yang Zhao, Hao Zhang

Firstly, we propose a feature quantity, role share, consisting of four discriminate statuses for a certain unit based on its contribution to generalization.

Image Classification

Super-Resolving Compressed Video in Coding Chain

no code implementations26 Mar 2021 Dewang Hou, Yang Zhao, Yuyao Ye, Jiayu Yang, Jian Zhang, Ronggang Wang

Scaling and lossy coding are widely used in video transmission and storage.

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

1 code implementation19 Mar 2021 Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Yingyan Lin

To design HW-NAS-Bench, we carefully collected the measured/estimated hardware performance of all the networks in the search spaces of both NAS-Bench-201 and FBNet, on six hardware devices that fall into three categories (i. e., commercial edge devices, FPGA, and ASIC).

Neural Architecture Search

Quantitative Effectiveness Assessment and Role Categorization of Individual Units in Convolutional Neural Networks

no code implementations17 Mar 2021 Yang Zhao, Hao Zhang

Identifying the roles of individual units is critical for understanding the mechanism of convolutional neural networks (CNNs).

Classification General Classification +1

Interaction between optical pulse and tumor using finite element analysis

no code implementations19 Jan 2021 Xianlin Song, Ao Teng, Jianshuang Wei, Hao Chen, Yang Zhao, Jianheng Chen, Fangwei Liu, Qianxiang Wan, Guoning Huang, Lingfang Song, Aojie Zhao, Bo Li, Zihao Li, Qiming He, Jinhong Zhang

As a non-destructive biological tissue imaging technology, photoacoustic imaging has important application value in the field of biomedicine.

Biological Physics

Waveform and Beamforming Design for Intelligent Reflecting Surface Aided Wireless Power Transfer: Single-User and Multi-User Solutions

no code implementations7 Jan 2021 Zhenyuan Feng, Bruno Clerckx, Yang Zhao

This paper highlights the fact that IRS can provide an extra passive beamforming gain on output DC power over conventional WPT designs and significantly influence the waveform design by leveraging the benefit of passive beamforming, frequency diversity and energy harvester nonlinearity.

Information Theory Signal Processing Information Theory

SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training

1 code implementation4 Jan 2021 Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang

Results show that: 1) applied to inference, SD achieves up to 2. 44x energy efficiency as evaluated via real hardware implementations; 2) applied to training, SD leads to 10. 56x and 4. 48x reduction in the storage and training energy, with negligible accuracy loss compared to state-of-the-art training baselines.

SDA: Improving Text Generation with Self Data Augmentation

no code implementations2 Jan 2021 Ping Yu, Ruiyi Zhang, Yang Zhao, Yizhe Zhang, Chunyuan Li, Changyou Chen

Data augmentation has been widely used to improve deep neural networks in many research fields, such as computer vision.

Data Augmentation Imitation Learning +1

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark

no code implementations ICLR 2021 Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin

To design HW-NAS-Bench, we carefully collected the measured/estimated hardware performance (e. g., energy cost and latency) of all the networks in the search space of both NAS-Bench-201 and FBNet, considering six hardware devices that fall into three categories (i. e., commercial edge devices, FPGA, and ASIC).

Neural Architecture Search

Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling

no code implementations ICLR 2021 Yang Zhao, Jianwen Xie, Ping Li

Energy-based models (EBMs) for generative modeling parametrize a single net and can be directly trained by maximum likelihood estimation.

Unsupervised Image-To-Image Translation

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training

1 code implementation NeurIPS 2020 Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin

Recent breakthroughs in deep neural networks (DNNs) have fueled a tremendous demand for intelligent edge devices featuring on-site learning, while the practical realization of such systems remains a challenge due to the limited resources available at the edge and the required massive training costs for state-of-the-art (SOTA) DNNs.

Quantization

A Comprehensive Survey of 6G Wireless Communications

no code implementations21 Dec 2020 Yang Zhao, Wenchao Zhai, Jun Zhao, Tinghao Zhang, Sumei Sun, Dusit Niyato, Kwok-Yan Lam

First, we give an overview of 6G from perspectives of technologies, security and privacy, and applications.

Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks

no code implementations20 Dec 2020 Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang

Massive account registration has raised concerns on risk management in e-commerce companies, especially when registration increases rapidly within a short time frame.

IRS-Aided SWIPT: Joint Waveform, Active and Passive Beamforming Design Under Nonlinear Harvester Model

1 code implementation10 Dec 2020 Yang Zhao, Bruno Clerckx, Zhenyuan Feng

To facilitate practical implementation, we also propose a low-complexity design based on closed-form adaptive waveform schemes.

Information Theory Signal Processing Information Theory

ReMP: Rectified Metric Propagation for Few-Shot Learning

no code implementations2 Dec 2020 Yang Zhao, Chunyuan Li, Ping Yu, Changyou Chen

Few-shot learning features the capability of generalizing from a few examples.

Few-Shot Learning

Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity

no code implementations COLING 2020 Yang Zhao, Lu Xiang, Junnan Zhu, Jiajun Zhang, Yu Zhou, Chengqing Zong

Previous studies combining knowledge graph (KG) with neural machine translation (NMT) have two problems: i) Knowledge under-utilization: they only focus on the entities that appear in both KG and training sentence pairs, making much knowledge in KG unable to be fully utilized.

Machine Translation Multi-Task Learning

Unpaired Image-to-Image Translation via Latent Energy Transport

1 code implementation CVPR 2021 Yang Zhao, Changyou Chen

Instead of explicitly extracting the two codes and applying adaptive instance normalization to combine them, our latent EBM can implicitly learn to transport the source style code to the target style code while preserving the content code, an advantage over existing image translation methods.

Image Reconstruction Image-to-Image Translation

Rethinking deinterlacing for early interlaced videos

no code implementations27 Nov 2020 Yang Zhao, Wei Jia, Ronggang Wang

Traditional deinterlacing approaches are mainly focused on early interlacing scanning systems and thus cannot handle the complex and complicated artifacts in real-world early interlaced videos.

Image Restoration

xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs

no code implementations24 Nov 2020 Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang

At online retail platforms, it is crucial to actively detect risks of fraudulent transactions to improve our customer experience, minimize loss, and prevent unauthorized chargebacks.

Graph Embedding

Deconstruct to Reconstruct a Configurable Evaluation Metric for Open-Domain Dialogue Systems

1 code implementation COLING 2020 Vitou Phy, Yang Zhao, Akiko Aizawa

For instance, specificity is mandatory in a food-ordering dialogue task, whereas fluency is preferred in a language-teaching dialogue system.

Semantic Similarity Semantic Textual Similarity

FaultNet: A Deep Convolutional Neural Network for bearing fault classification

1 code implementation5 Oct 2020 Rishikesh Magar, Lalit Ghule, Junhan Li, Yang Zhao, Amir Barati Farimani

In this work, we analyze vibration signal data of mechanical systems with bearings by combining different signal processing methods and coupling them with machine learning techniques to classify different types of bearing faults.

Classification Fault Detection +1

Structure-Aware Human-Action Generation

1 code implementation ECCV 2020 Ping Yu, Yang Zhao, Chunyuan Li, Junsong Yuan, Changyou Chen

Generating long-range skeleton-based human actions has been a challenging problem since small deviations of one frame can cause a malformed action sequence.

Action Generation graph construction +1

Attacks to Federated Learning: Responsive Web User Interface to Recover Training Data from User Gradients

no code implementations8 Jun 2020 Hans Albert Lianto, Yang Zhao, Jun Zhao

In a case where the aggregator is untrusted and LDP is not applied to each user gradient, the aggregator can recover sensitive user data from these gradients.

Federated Learning

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

no code implementations7 May 2020 Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin

We present SmartExchange, an algorithm-hardware co-design framework to trade higher-cost memory storage/access for lower-cost computation, for energy-efficient inference of deep neural networks (DNNs).

Model Compression Quantization

TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators Towards Local and in Time Domain

no code implementations3 May 2020 Weitao Li, Pengfei Xu, Yang Zhao, Haitong Li, Yuan Xie, Yingyan Lin

Resistive-random-access-memory (ReRAM) based processing-in-memory (R$^2$PIM) accelerators show promise in bridging the gap between Internet of Thing devices' constrained resources and Convolutional/Deep Neural Networks' (CNNs/DNNs') prohibitive energy cost.

Bayesian Meta Sampling for Fast Uncertainty Adaptation

1 code implementation ICLR 2020 Zhenyi Wang, Yang Zhao, Ping Yu, Ruiyi Zhang, Changyou Chen

Specifically, we propose a Bayesian meta sampling framework consisting of two main components: a meta sampler and a sample adapter.

Meta-Learning

Local Differential Privacy based Federated Learning for Internet of Things

no code implementations19 Apr 2020 Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam

To avoid the privacy threat and reduce the communication cost, in this paper, we propose to integrate federated learning and local differential privacy (LDP) to facilitate the crowdsourcing applications to achieve the machine learning model.

Federated Learning

Dual-discriminator GAN: A GAN way of profile face recognition

no code implementations20 Mar 2020 Xin-Yu Zhang, Yang Zhao, Hao Zhang

A wealth of angle problems occur when facial recognition is performed: At present, the feature extraction network presents eigenvectors with large differences between the frontal face and profile face recognition of the same person in many cases.

Face Recognition

A New MRAM-based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision

no code implementations2 Mar 2020 Hongjie Wang, Yang Zhao, Chaojian Li, Yue Wang, Yingyan Lin

The excellent performance of modern deep neural networks (DNNs) comes at an often prohibitive training cost, limiting the rapid development of DNN innovations and raising various environmental concerns.

DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures

no code implementations26 Feb 2020 Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, Yingyan Lin

The recent breakthroughs in deep neural networks (DNNs) have spurred a tremendously increased demand for DNN accelerators.

Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences

1 code implementation CVPR 2020 Zhu Zhang, Zhou Zhao, Yang Zhao, Qi. Wang, Huasheng Liu, Lianli Gao

In this paper, we consider a novel task, Spatio-Temporal Video Grounding for Multi-Form Sentences (STVG).

AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs

1 code implementation6 Jan 2020 Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, Yingyan Lin

Specifically, AutoDNNchip consists of two integrated enablers: (1) a Chip Predictor, built on top of a graph-based accelerator representation, which can accurately and efficiently predict a DNN accelerator's energy, throughput, and area based on the DNN model parameters, hardware configuration, technology-based IPs, and platform constraints; and (2) a Chip Builder, which can automatically explore the design space of DNN chips (including IP selection, block configuration, resource balancing, etc.

Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions

1 code implementation AAAI 2019 Zhenyi Wang, Ping Yu, Yang Zhao, Ruiyi Zhang, Yufan Zhou, Junsong Yuan, Changyou Chen

In this paper, we focus on skeleton-based action generation and propose to model smooth and diverse transitions on a latent space of action sequences with much lower dimensionality.

Action Generation

Patchy Image Structure Classification Using Multi-Orientation Region Transform

1 code implementation2 Dec 2019 Xiaohan Yu, Yang Zhao, Yongsheng Gao, Shengwu Xiong, Xiaohui Yuan

To address above limitations, this paper proposes a novel Multi-Orientation Region Transform (MORT), which can effectively characterize both contour and structure features simultaneously, for patchy image structure classification.

Classification General Classification

A Deep Gradient Boosting Network for Optic Disc and Cup Segmentation

no code implementations5 Nov 2019 Qing Liu, Beiji Zou, Yang Zhao, Yixiong Liang

To build connections among prediction branches, this paper introduces gradient boosting framework to deep classification model and proposes a gradient boosting network called BoostNet.

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings

no code implementations NeurIPS 2019 Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang

Extensive simulations and ablation studies, with real energy measurements from an FPGA board, confirm the superiority of our proposed strategies and demonstrate remarkable energy savings for training.

DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition

no code implementations10 Oct 2019 Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang

Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing problem.

Deep High-Resolution Representation Learning for Visual Recognition

25 code implementations20 Aug 2019 Jingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, Xinggang Wang, Wenyu Liu, Bin Xiao

High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection.

Instance Segmentation Object Detection +3

MobileFAN: Transferring Deep Hidden Representation for Face Alignment

no code implementations11 Aug 2019 Yang Zhao, Yifan Liu, Chunhua Shen, Yongsheng Gao, Shengwu Xiong

To this end, we propose an effective lightweight model, namely Mobile Face Alignment Network (MobileFAN), using a simple backbone MobileNetV2 as the encoder and three deconvolutional layers as the decoder.

Face Alignment Facial Landmark Detection

Unsupervised Rewriter for Multi-Sentence Compression

no code implementations ACL 2019 Yang Zhao, Xiaoyu Shen, Wei Bi, Akiko Aizawa

First, the word graph approach that simply concatenates fragments from multiple sentences may yield non-fluent or ungrammatical compression.

Sentence Compression

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

no code implementations26 Jun 2019 Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li, Lingjuan Lyu, Yingbo Liu

To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' data.

Edge-computing Federated Learning

Synchronous Bidirectional Inference for Neural Sequence Generation

1 code implementation24 Feb 2019 Jiajun Zhang, Long Zhou, Yang Zhao, Cheng-qing Zong

In this work, we propose a synchronous bidirectional inference model to generate outputs using both left-to-right and right-to-left decoding simultaneously and interactively.

Abstractive Text Summarization Machine Translation

Self-Adversarially Learned Bayesian Sampling

no code implementations21 Nov 2018 Yang Zhao, Jianyi Zhang, Changyou Chen

Scalable Bayesian sampling is playing an important role in modern machine learning, especially in the fast-developed unsupervised-(deep)-learning models.

Variance Reduction in Stochastic Particle-Optimization Sampling

no code implementations ICML 2020 Jianyi Zhang, Yang Zhao, Changyou Chen

Stochastic particle-optimization sampling (SPOS) is a recently-developed scalable Bayesian sampling framework that unifies stochastic gradient MCMC (SG-MCMC) and Stein variational gradient descent (SVGD) algorithms based on Wasserstein gradient flows.

POS

Addressing Troublesome Words in Neural Machine Translation

no code implementations EMNLP 2018 Yang Zhao, Jiajun Zhang, Zhongjun He, Cheng-qing Zong, Hua Wu

One of the weaknesses of Neural Machine Translation (NMT) is in handling lowfrequency and ambiguous words, which we refer as troublesome words.

Machine Translation

Random Occlusion-recovery for Person Re-identification

no code implementations26 Sep 2018 Di Wu, Kun Zhang, Fei Cheng, Yang Zhao, Qi Liu, Chang-An Yuan, De-Shuang Huang

As a basic task of multi-camera surveillance system, person re-identification aims to re-identify a query pedestrian observed from non-overlapping multiple cameras or across different time with a single camera.

Person Re-Identification

A Language Model based Evaluator for Sentence Compression

no code implementations ACL 2018 Yang Zhao, Zhiyuan Luo, Akiko Aizawa

We herein present a language-model-based evaluator for deletion-based sentence compression and view this task as a series of deletion-and-evaluation operations using the evaluator.

Language Modelling Sentence Compression

Multispectral Image Intrinsic Decomposition via Subspace Constraint

no code implementations CVPR 2018 Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Cao

In this paper, a new Multispectral Image Intrinsic Decomposition model (MIID) is presented to decompose the shading and reflectance from a single multispectral image.

Phrase Table as Recommendation Memory for Neural Machine Translation

no code implementations25 May 2018 Yang Zhao, Yining Wang, Jiajun Zhang, Cheng-qing Zong

Neural Machine Translation (NMT) has drawn much attention due to its promising translation performance recently.

Machine Translation

Multispectral Image Intrinsic Decomposition via Low Rank Constraint

no code implementations24 Feb 2018 Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Cao

In this paper, a Low Rank Multispectral Image Intrinsic Decomposition model (LRIID) is presented to decompose the shading and reflectance from a single multispectral image.

Towards Neural Machine Translation with Partially Aligned Corpora

no code implementations IJCNLP 2017 Yining Wang, Yang Zhao, Jiajun Zhang, Cheng-qing Zong, Zhengshan Xue

While neural machine translation (NMT) has become the new paradigm, the parameter optimization requires large-scale parallel data which is scarce in many domains and language pairs.

Machine Translation

GUN: Gradual Upsampling Network for Single Image Super-Resolution

no code implementations13 Mar 2017 Yang Zhao, Guoqing Li, Wenjun Xie, Wei Jia, Hai Min, Xiaoping Liu

The GUN consists of an input layer, multiple upsampling and convolutional layers, and an output layer.

Image Super-Resolution

Parallel Spectral Clustering Algorithm Based on Hadoop

no code implementations31 May 2015 Yajun Cui, Yang Zhao, Kafei Xiao, Chenglong Zhang, Lei Wang

Spectral clustering and cloud computing is emerging branch of computer science or related discipline.

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