Search Results for author: Zhiqiang Zhang

Found 49 papers, 16 papers with code

Long-tail Augmented Graph Contrastive Learning for Recommendation

1 code implementation20 Sep 2023 Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou

To make the data augmentation schema learnable, we design an auto drop module to generate pseudo-tail nodes from head nodes and a knowledge transfer module to reconstruct the head nodes from pseudo-tail nodes.

Contrastive Learning Data Augmentation +2

BATINet: Background-Aware Text to Image Synthesis and Manipulation Network

no code implementations11 Aug 2023 Ryugo Morita, Zhiqiang Zhang, Jinjia Zhou

We proposed a Background-Aware Text to Image synthesis and manipulation Network (BATINet), which contains two key components: Position Detect Network (PDN) and Harmonize Network (HN).

Image Generation Image Manipulation

Generative Contrastive Graph Learning for Recommendation

1 code implementation11 Jul 2023 Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang

Second, feature augmentation imposes the same scale noise augmentation on each node, which neglects the unique characteristics of nodes on the graph.

Collaborative Filtering Contrastive Learning +3

A Physics-Informed Low-Shot Learning For sEMG-Based Estimation of Muscle Force and Joint Kinematics

no code implementations8 Jul 2023 Yue Shi, Shuhao Ma, Yihui Zhao, Zhiqiang Zhang

This method seamlessly integrates Lagrange's equation of motion and inverse dynamic muscle model into the generative adversarial network (GAN) framework for structured feature decoding and extrapolated estimation from the small sample data.

InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs

no code implementations1 Jul 2023 Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou

Inspired by the philosophy of ``think-like-a-vertex", a GAS-like (Gather-Apply-Scatter) schema is proposed to describe the computation paradigm and data flow of GNN inference.


Differential Privacy May Have a Potential Optimization Effect on Some Swarm Intelligence Algorithms besides Privacy-preserving

no code implementations30 Jun 2023 Zhiqiang Zhang, Hong Zhu, Meiyi Xie

For this reason, this paper attempts to combine DP and SI for the first time, and proposes a general differentially private swarm intelligence algorithm framework (DPSIAF).

Metaheuristic Optimization Privacy Preserving

A Fast Fourier Convolutional Deep Neural Network For Accurate and Explainable Discrimination Of Wheat Yellow Rust And Nitrogen Deficiency From Sentinel-2 Time-Series Data

no code implementations29 Jun 2023 Yue Shi, Liangxiu Han, Pablo González-Moreno, Darren Dancey, Wenjiang Huang, Zhiqiang Zhang, Yuanyuan Liu, Mengning Huan, Hong Miao, Min Dai

Specifically, unlike the existing CNN models, the main components of the proposed model include: 1) a fast Fourier convolutional block, a newly fast Fourier transformation kernel as the basic perception unit, to substitute the traditional convolutional kernel to capture both local and global responses to plant stress in various time-scale and improve computing efficiency with reduced learning parameters in Fourier domain; 2) Capsule Feature Encoder to encapsulate the extracted features into a series of vector features to represent part-to-whole relationship with the hierarchical structure of the host-stress interactions of the specific stress.

Time Series

Description-Enhanced Label Embedding Contrastive Learning for Text Classification

1 code implementation15 Jun 2023 Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang

Then, we propose a novel Relation of Relation Learning Network (R2-Net) for text classification, in which text classification and R2 classification are treated as optimization targets.

Contrastive Learning Self-Supervised Learning +2

Who Would be Interested in Services? An Entity Graph Learning System for User Targeting

no code implementations30 May 2023 Dan Yang, Binbin Hu, Xiaoyan Yang, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Guannan Zhang

At the online stage, the system offers the ability of user targeting in real-time based on the entity graph from the offline stage.

graph construction Graph Learning

COUPA: An Industrial Recommender System for Online to Offline Service Platforms

no code implementations25 Apr 2023 Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou

Aiming at helping users locally discovery retail services (e. g., entertainment and dinning), Online to Offline (O2O) service platforms have become popular in recent years, which greatly challenge current recommender systems.

Recommendation Systems

GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning

no code implementations25 Apr 2023 Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou

At last, we conduct extensive experiments on both offline and online environments, which demonstrates the superior capability of GARCIA in improving tail queries and overall performance in service search scenarios.

Contrastive Learning Transfer Learning

Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning

no code implementations24 Mar 2023 Bikun Wang, Zhipeng Wang, Chenhao Zhu, Zhiqiang Zhang, Zhichen Wang, Penghong Lin, Jingchu Liu, Qian Zhang

We evaluate our method both in closed-loop simulation and real world driving, and demonstrate the neural network planner has outstanding performance in complex urban autonomous driving scenarios.

Autonomous Driving Imitation Learning +1

Interactive Image Manipulation with Complex Text Instructions

no code implementations25 Nov 2022 Ryugo Morita, Zhiqiang Zhang, Man M. Ho, Jinjia Zhou

To solve these problems, we propose a novel image manipulation method that interactively edits an image using complex text instructions.

Descriptive Image Manipulation +1

Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification

no code implementations13 Aug 2022 Xin Wang, Heng Chang, Beini Xie, Tian Bian, Shiji Zhou, Daixin Wang, Zhiqiang Zhang, Wenwu Zhu

Graph neural networks (GNNs) have achieved tremendous success in the task of graph classification and its diverse downstream real-world applications.

Graph Classification

KGNN: Distributed Framework for Graph Neural Knowledge Representation

no code implementations17 May 2022 Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou, Chuan Shi

Knowledge representation learning has been commonly adopted to incorporate knowledge graph (KG) into various online services.

Link Prediction Representation Learning

CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space

1 code implementation23 Apr 2022 Yupeng Hou, Binbin Hu, Zhiqiang Zhang, Wayne Xin Zhao

Session-based Recommendation (SBR) refers to the task of predicting the next item based on short-term user behaviors within an anonymous session.

Session-Based Recommendations

Neural Graph Matching for Pre-training Graph Neural Networks

1 code implementation3 Mar 2022 Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen

In this way, we can learn adaptive representations for a given graph when paired with different graphs, and both node- and graph-level characteristics are naturally considered in a single pre-training task.

Graph Matching

An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022

1 code implementation1 Mar 2022 Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi

Temporal link prediction, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area.

Graph Learning Link Prediction

Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift

no code implementations27 Jan 2022 Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou

To this end, in this paper, we propose a novel Distribution Recovered Graph Self-Training framework (DR-GST), which could recover the distribution of the original labeled dataset.

Variational Inference

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback

1 code implementation28 Dec 2021 Boxin Zhao, Lingxiao Wang, Mladen Kolar, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Chaochao Chen

As a result, client sampling plays an important role in FL systems as it affects the convergence rate of optimization algorithms used to train machine learning models.

Federated Learning Stochastic Optimization

MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data

no code implementations NeurIPS 2021 Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, Jianyong Zhou

Time series forecasting is widely used in business intelligence, e. g., forecast stock market price, sales, and help the analysis of data trend.

Time Series Time Series Forecasting

SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation

no code implementations18 Aug 2021 Kai Zhang, Hao Qian, Qi Liu, Zhiqiang Zhang, Jun Zhou, Jianhui Ma, Enhong Chen

Specifically, we first encode user/item reviews via BERT and propose a light-weighted sentiment learner to extract semantic features of each review.

Recommendation Systems

Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure

1 code implementation2 Mar 2021 Jin Chen, Tiezheng Ge, Gangwei Jiang, Zhiqiang Zhang, Defu Lian, Kai Zheng

Based on the tree structure, Thompson sampling is adapted with dynamic programming, leading to efficient exploration for potential ad creatives with the largest CTR.

Efficient Exploration Thompson Sampling

Automated Creative Optimization for E-Commerce Advertising

1 code implementation28 Feb 2021 Jin Chen, Ju Xu, Gangwei Jiang, Tiezheng Ge, Zhiqiang Zhang, Defu Lian, Kai Zheng

However, interactions between creative elements may be more complex than the inner product, and the FM-estimated CTR may be of high variance due to limited feedback.

AutoML Click-Through Rate Prediction +2

LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign

no code implementations3 Feb 2021 Tianchi Cai, Daxi Cheng, Chen Liang, Ziqi Liu, Lihong Gu, Huizhi Xie, Zhiqiang Zhang, Xiaodong Zeng, Jinjie Gu

In this paper, we analyze the network A/B testing problem under a real-world online marketing campaign, describe our proposed LinkLouvain method, and evaluate it on real-world data.

Link Prediction Marketing

Bandit Samplers for Training Graph Neural Networks

2 code implementations NeurIPS 2020 Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi

However, due to the intractable computation of optimal sampling distribution, these sampling algorithms are suboptimal for GCNs and are not applicable to more general graph neural networks (GNNs) where the message aggregator contains learned weights rather than fixed weights, such as Graph Attention Networks (GAT).

Graph Attention

ATBRG: Adaptive Target-Behavior Relational Graph Network for Effective Recommendation

no code implementations25 May 2020 Yufei Feng, Binbin Hu, Fuyu Lv, Qingwen Liu, Zhiqiang Zhang, Wenwu Ou

Specifically, to associate the given target item with user behaviors over KG, we propose the graph connect and graph prune techniques to construct adaptive target-behavior relational graph.

Recommendation Systems

A Natural Language Processing Pipeline of Chinese Free-text Radiology Reports for Liver Cancer Diagnosis

no code implementations10 Apr 2020 Honglei Liu, Yan Xu, Zhiqiang Zhang, Ni Wang, Yanqun Huang, Yanjun Hu, Zhenghan Yang, Rui Jiang, Hui Chen

Despite the rapid development of natural language processing (NLP) implementation in electronic medical records (EMRs), Chinese EMRs processing remains challenging due to the limited corpus and specific grammatical characteristics, especially for radiology reports.

Computed Tomography (CT) Coreference Resolution +3

NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay

no code implementations1 Apr 2020 Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan Qi

Considering the above challenges and the special scenario in Ant Financial, we try to incorporate default prediction with network information to alleviate the cold-start problem.

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

no code implementations27 Feb 2020 Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi

In this paper, we present a graph representation learning method atop of transaction networks for merchant incentive optimization in mobile payment marketing.

Graph Representation Learning Marketing

DSSLP: A Distributed Framework for Semi-supervised Link Prediction

no code implementations27 Feb 2020 Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou

Instead of training model on the whole graph, DSSLP is proposed to train on the \emph{$k$-hops neighborhood} of nodes in a mini-batch setting, which helps reduce the scale of the input graph and distribute the training procedure.

Link Prediction

Real-Time Semantic Segmentation via Multiply Spatial Fusion Network

no code implementations17 Nov 2019 Haiyang Si, Zhiqiang Zhang, Feifan Lv, Gang Yu, Feng Lu

Specifically, it achieves 77. 1% Mean IOU on the Cityscapes test dataset with the speed of 41 FPS for a 1024*2048 input, and 75. 4% Mean IOU with the speed of 91 FPS on the Camvid test dataset.

Autonomous Driving Playing the Game of 2048 +1

Spectrogram-frame linear network and continuous frame sequence for bird sound classification

1 code implementation Ecological Informatics 2019 Xin Zhang, Aibin Chen, Guoxiong Zhou, Zhiqiang Zhang, Xibei Huang, Xiaohu Qiang

Inspired by that bird sound has various frequency distributions and continuous time-varying properties, a novel method is proposed for the classification of bird sound based on continuous frame sequence and spectrogram-frame linear network (SFLN).

Sound Classification

Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation

no code implementations IJCNLP 2019 Zhangming Chan, Xiuying Chen, Yongliang Wang, Juntao Li, Zhiqiang Zhang, Kun Gai, Dongyan Zhao, Rui Yan

Different from other text generation tasks, in product description generation, it is of vital importance to generate faithful descriptions that stick to the product attribute information.

Text Generation

Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder

no code implementations26 Mar 2019 Yuchi Zhang, Yongliang Wang, Liping Zhang, Zhiqiang Zhang, Kun Gai

In fact, this objective term guides the encoder towards the "best encoder" of the decoder to enhance the expressiveness.

Text Generation

Semantic Human Matting

2 code implementations5 Sep 2018 Quan Chen, Tiezheng Ge, Yanyu Xu, Zhiqiang Zhang, Xinxin Yang, Kun Gai

SHM is the first algorithm that learns to jointly fit both semantic information and high quality details with deep networks.

Image Matting

Cascaded Pyramid Network for Multi-Person Pose Estimation

5 code implementations CVPR 2018 Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, Jian Sun

In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.

Keypoint Detection Multi-Person Pose Estimation

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