Search Results for author: wei he

Found 40 papers, 14 papers with code

Learning by Consuming: Optimal Pricing with Endogenous Information Provision

no code implementations3 Sep 2022 Huiyi Guo, wei he, Bin Liu

We study the revenue-maximizing mechanism when a buyer's value evolves endogenously because of learning-by-consuming.

The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network

no code implementations16 Jul 2022 Zhongzhan Huang, Senwei Liang, Mingfu Liang, wei he, Haizhao Yang, Liang Lin

Recently many plug-and-play self-attention modules (SAMs) are proposed to enhance the model generalization by exploiting the internal information of deep convolutional neural networks (CNNs).

Crowd Counting

Enhancing Sequential Recommendation with Graph Contrastive Learning

no code implementations30 May 2022 Yixin Zhang, Yong liu, Yonghui Xu, Hao Xiong, Chenyi Lei, wei he, Lizhen Cui, Chunyan Miao

Specifically, GCL4SR employs a Weighted Item Transition Graph (WITG), built based on interaction sequences of all users, to provide global context information for each interaction and weaken the noise information in the sequence data.

Auxiliary Learning Contrastive Learning +1

BMD: A General Class-balanced Multicentric Dynamic Prototype Strategy for Source-free Domain Adaptation

1 code implementation6 Apr 2022 Sanqing Qu, Guang Chen, Jing Zhang, Zhijun Li, wei he, DaCheng Tao

Source-free Domain Adaptation (SFDA) aims to adapt a pre-trained source model to the unlabeled target domain without accessing the well-labeled source data, which is a much more practical setting due to the data privacy, security, and transmission issues.

Domain Adaptation pseudo label

Uncovering the dynamic effects of DEX treatment on lung cancer by integrating bioinformatic inference and multiscale modeling of scRNA-seq and proteomics data

no code implementations1 Mar 2022 Minghan Chen, Chunrui Xu, Ziang Xu, wei he, Haorui Zhang, Jing Su, Qianqian Song

Those genes involved in the TGF-\b{eta} pathway and their crosstalk with the ERBB pathway presented a strong survival prognosis in clinical lung cancer samples.

Time Series

AlterSGD: Finding Flat Minima for Continual Learning by Alternative Training

no code implementations13 Jul 2021 Zhongzhan Huang, Mingfu Liang, Senwei Liang, wei he

Deep neural networks suffer from catastrophic forgetting when learning multiple knowledge sequentially, and a growing number of approaches have been proposed to mitigate this problem.

Continual Learning Semantic Segmentation

Blending Pruning Criteria for Convolutional Neural Networks

no code implementations11 Jul 2021 wei he, Zhongzhan Huang, Mingfu Liang, Senwei Liang, Haizhao Yang

One filter could be important according to a certain criterion, while it is unnecessary according to another one, which indicates that each criterion is only a partial view of the comprehensive "importance".

Network Pruning

Characterization of equilibrium existence and purification in general Bayesian games

no code implementations16 Jun 2021 wei he, Xiang Sun, Yeneng Sun, Yishu Zeng

This paper studies Bayesian games with general action spaces, correlated types and interdependent payoffs.

From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search

no code implementations24 Mar 2021 Rui Li, Yunjiang Jiang, WenYun Yang, Guoyu Tang, Songlin Wang, Chaoyi Ma, wei he, Xi Xiong, Yun Xiao, Eric Yihong Zhao

We introduce deep learning models to the two most important stages in product search at JD. com, one of the largest e-commerce platforms in the world.

Re-Ranking Semantic Retrieval

Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing

no code implementations2 Mar 2021 Danfeng Hong, wei he, Naoto Yokoya, Jing Yao, Lianru Gao, Liangpei Zhang, Jocelyn Chanussot, Xiao Xiang Zhu

Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS).

CAP: Context-Aware Pruning for Semantic-Segmentation

1 code implementation6 Jan 2021 wei he, Meiqing Wu, Mingfu Liang, Siew-Kei Lam

In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework.

Network Pruning Semantic Segmentation

CAP-Context-Aware-Pruning-for-Semantic-Segmentation

1 code implementation6 Jan 2021 wei he, Meiqing Wu, Mingfu Liang, Siew-Kei Lam

In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework.

Network Pruning Semantic Segmentation

Improving robustness of softmax corss-entropy loss via inference information

no code implementations1 Jan 2021 Bingbing Song, wei he, Renyang Liu, Shui Yu, Ruxin Wang, Mingming Gong, Tongliang Liu, Wei Zhou

Several state-of-the-arts start from improving the inter-class separability of training samples by modifying loss functions, where we argue that the adversarial samples are ignored and thus limited robustness to adversarial attacks is resulted.

Fast Hyperspectral Image Recovery via Non-iterative Fusion of Dual-Camera Compressive Hyperspectral Imaging

no code implementations30 Dec 2020 wei he, Naoto Yokoya, Xin Yuan

Specifically, the RGB measurement is utilized to estimate the coefficients, meanwhile the CASSI measurement is adopted to provide the orthogonal spectral basis.

Site-Specific Structure at Multiple Length Scales in Kagome Quantum Spin Liquid Candidates

no code implementations14 Dec 2020 Rebecca W. Smaha, Idris Boukahil, Charles J. Titus, Jack Mingde Jiang, John P. Sheckelton, wei he, Jiajia Wen, John Vinson, Suyin Grass Wang, Yu-Sheng Chen, Simon J. Teat, Thomas P. Devereaux, C. Das Pemmaraju, Young S. Lee

Realizing a quantum spin liquid (QSL) ground state in a real material is a leading issue in condensed matter physics research.

Strongly Correlated Electrons Materials Science

Efficient Attention Network: Accelerate Attention by Searching Where to Plug

1 code implementation28 Nov 2020 Zhongzhan Huang, Senwei Liang, Mingfu Liang, wei he, Haizhao Yang

Recently, many plug-and-play self-attention modules are proposed to enhance the model generalization by exploiting the internal information of deep convolutional neural networks (CNNs).

Unmixing Convolutional Features for Crisp Edge Detection

1 code implementation19 Nov 2020 Linxi Huan, Nan Xue, Xianwei Zheng, wei he, Jianya Gong, Gui-Song Xia

This paper presents a context-aware tracing strategy (CATS) for crisp edge detection with deep edge detectors, based on an observation that the localization ambiguity of deep edge detectors is mainly caused by the mixing phenomenon of convolutional neural networks: feature mixing in edge classification and side mixing during fusing side predictions.

BSDS500 Edge Classification +1

Nonlinear Cooperative Control of Double Drone-Bar Transportation System

no code implementations15 Nov 2020 Peng Zhang, Yongchun Fang, Xiao Liang, He Lin, wei he

Due to the limitation of the drone's load capacity, various specific tasks need to be accomplished by multiple drones in collaboration.

Dynamical Systems Systems and Control Systems and Control

Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

1 code implementation24 Oct 2020 wei he, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan zhang, Liangpei Zhang

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting.

Denoising Image Restoration

A Network-Guided Reaction-Diffusion Model of AT[N] Biomarkers in Alzheimer's Disease

no code implementations10 Sep 2020 Jingwen Zhang, Defu Yang, wei he, Guorong Wu, Minghan Chen

Currently, many studies of Alzheimer's disease (AD) are investigating the neurobiological factors behind the acquisition of beta-amyloid (A), pathologic tau (T), and neurodegeneration ([N]) biomarkers from neuroimages.

Illumination invariant hyperspectral image unmixing based on a digital surface model

no code implementations23 Jul 2020 Tatsumi Uezato, Naoto Yokoya, wei he

Although many spectral unmixing models have been developed to address spectral variability caused by variable incident illuminations, the mechanism of the spectral variability is still unclear.

Guided Deep Decoder: Unsupervised Image Pair Fusion

1 code implementation ECCV 2020 Tatsumi Uezato, Danfeng Hong, Naoto Yokoya, wei he

The proposed network is composed of an encoder-decoder network that exploits multi-scale features of a guidance image and a deep decoder network that generates an output image.

Pansharpening

Breaking the Limits of Remote Sensing by Simulation and Deep Learning for Flood and Debris Flow Mapping

1 code implementation9 Jun 2020 Naoto Yokoya, Kazuki Yamanoi, wei he, Gerald Baier, Bruno Adriano, Hiroyuki Miura, Satoru Oishi

We propose a framework that estimates inundation depth (maximum water level) and debris-flow-induced topographic deformation from remote sensing imagery by integrating deep learning and numerical simulation.

Change Detection

Hyperspectral Super-Resolution via Coupled Tensor Ring Factorization

no code implementations6 Jan 2020 Wei He, Yong Chen, Naoto Yokoya, Chao Li, Qibin Zhao

In this paper, we propose a new model, named coupled tensor ring factorization (CTRF), for HSR.

Super-Resolution

Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising

2 code implementations CVPR 2019 Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao

This is done by first learning a low-dimensional projection and the related reduced image from the noisy HSI.

Denoising

Answer-focused and Position-aware Neural Question Generation

no code implementations EMNLP 2018 Xingwu Sun, Jing Liu, Yajuan Lyu, wei he, Yanjun Ma, Shi Wang

(2) The model copies the context words that are far from and irrelevant to the answer, instead of the words that are close and relevant to the answer.

Machine Reading Comprehension Question Answering +1

Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes

no code implementations30 Jul 2018 Xianyan Jia, Shutao Song, wei he, Yangzihao Wang, Haidong Rong, Feihu Zhou, Liqiang Xie, Zhenyu Guo, Yuanzhou Yang, Liwei Yu, Tiegang Chen, Guangxiao Hu, Shaohuai Shi, Xiaowen Chu

(3) We propose highly optimized all-reduce algorithms that achieve up to 3x and 11x speedup on AlexNet and ResNet-50 respectively than NCCL-based training on a cluster with 1024 Tesla P40 GPUs.

2048

Multi-temporal Sentinel-1 and -2 Data Fusion for Optical Image Simulation

no code implementations26 Jul 2018 Wei He, Naoto Yokoya

In this paper, we present the optical image simulation from a synthetic aperture radar (SAR) data using deep learning based methods.

Cloud Removal

Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification

no code implementations ACL 2018 Yizhong Wang, Kai Liu, Jing Liu, wei he, Yajuan Lyu, Hua Wu, Sujian Li, Haifeng Wang

Machine reading comprehension (MRC) on real web data usually requires the machine to answer a question by analyzing multiple passages retrieved by search engine.

Machine Reading Comprehension Question Answering

A New Method of Region Embedding for Text Classification

1 code implementation ICLR 2018 chao qiao, Bo Huang, guocheng niu, daren li, daxiang dong, wei he, dianhai yu, Hua Wu

In this paper, we propose a new method of learning and utilizing task-specific distributed representations of n-grams, referred to as “region embeddings”.

Classification General Classification +2

DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

3 code implementations WS 2018 Wei He, Kai Liu, Jing Liu, Yajuan Lyu, Shiqi Zhao, Xinyan Xiao, Yu-An Liu, Yizhong Wang, Hua Wu, Qiaoqiao She, Xuan Liu, Tian Wu, Haifeng Wang

Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.

Machine Reading Comprehension

Semi-Supervised Learning for Neural Machine Translation

no code implementations ACL 2016 Yong Cheng, Wei Xu, Zhongjun He, wei he, Hua Wu, Maosong Sun, Yang Liu

While end-to-end neural machine translation (NMT) has made remarkable progress recently, NMT systems only rely on parallel corpora for parameter estimation.

Machine Translation Translation

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