Search Results for author: Zhao Li

Found 51 papers, 18 papers with code

HyCubE: Efficient Knowledge Hypergraph 3D Circular Convolutional Embedding

no code implementations14 Feb 2024 Zhao Li, Xin Wang, JianXin Li, Wenbin Guo, Jun Zhao

Existing knowledge hypergraph embedding methods mainly focused on improving model performance, but their model structures are becoming more complex and redundant.

hypergraph embedding

ConvD: Attention Enhanced Dynamic Convolutional Embeddings for Knowledge Graph Completion

no code implementations11 Dec 2023 Wenbin Guo, Zhao Li, Xin Wang, Zirui Chen

In this paper, we propose a novel dynamic convolutional embedding model ConvD for knowledge graph completion, which directly reshapes the relation embeddings into multiple internal convolution kernels to improve the external convolution kernels of the traditional convolutional embedding model.

Entity Embeddings Relation

Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection

no code implementations9 Dec 2023 Yuanchen Bei, Sheng Zhou, Qiaoyu Tan, Hao Xu, Hao Chen, Zhao Li, Jiajun Bu

To address these issues, we utilize the advantages of reinforcement learning in adaptively learning in complex environments and propose a novel method that incorporates Reinforcement neighborhood selection for unsupervised graph ANomaly Detection (RAND).

Graph Anomaly Detection Representation Learning

An empirical study of next-basket recommendations

no code implementations5 Dec 2023 Zhufeng Shao, Shoujin Wang, Qian Zhang, Wenpeng Lu, Zhao Li, Xueping Peng

This methodological rigor establishes a cohesive framework for the impartial evaluation of diverse NBR approaches.

Recommendation Systems

CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks

no code implementations6 Jul 2023 Yuanchen Bei, Hao Xu, Sheng Zhou, Huixuan Chi, Haishuai Wang, Mengdi Zhang, Zhao Li, Jiajun Bu

Dynamic graph data mining has gained popularity in recent years due to the rich information contained in dynamic graphs and their widespread use in the real world.

Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

no code implementations20 Jun 2023 Linyao Yang, Hongyang Chen, Zhao Li, Xiao Ding, Xindong Wu

Recently, ChatGPT, a representative large language model (LLM), has gained considerable attention due to its powerful emergent abilities.

Knowledge Graphs Language Modelling +1

Cold-Start based Multi-Scenario Ranking Model for Click-Through Rate Prediction

no code implementations16 Apr 2023 Peilin Chen, Hong Wen, Jing Zhang, Fuyu Lv, Zhao Li, Qijie Shen, Wanjie Tao, Ying Zhou, Chao Zhang

Online travel platforms (OTPs), e. g., Ctrip. com or Fliggy. com, can effectively provide travel-related products or services to users.

Click-Through Rate Prediction

GIPA: A General Information Propagation Algorithm for Graph Learning

1 code implementation19 Jan 2023 Houyi Li, Zhihong Chen, Zhao Li, Qinkai Zheng, Peng Zhang, Shuigeng Zhou

Specifically, the bit-wise correlation calculates the element-wise attention weight through a multi-layer perceptron (MLP) based on the dense representations of two nodes and their edge; The feature-wise correlation is based on the one-hot representations of node attribute features for feature selection.

Attribute feature selection +3

Context-Aware Robust Fine-Tuning

no code implementations29 Nov 2022 Xiaofeng Mao, Yuefeng Chen, Xiaojun Jia, Rong Zhang, Hui Xue, Zhao Li

Contrastive Language-Image Pre-trained (CLIP) models have zero-shot ability of classifying an image belonging to "[CLASS]" by using similarity between the image and the prompt sentence "a [CONTEXT] of [CLASS]".

Domain Generalization Sentence

Oscillatory cooperation prevalence emerges from misperception

no code implementations17 Oct 2022 Jing Zhang, Zhao Li, Jiqiang Zhang, Lin Ma, Guozhong Zheng, Li Chen

Here we show that oscillatory behaviors naturally emerge if incomplete information is incorporated into the cooperation evolution of a non-Markov model.

Defending Against Backdoor Attack on Graph Nerual Network by Explainability

no code implementations7 Sep 2022 Bingchen Jiang, Zhao Li

After identifying the malicious sample, the explainability of the GNN model can help us capture the most significant subgraph which is probably the trigger in a trojan graph.

Backdoor Attack Graph Classification

A Systematical Evaluation for Next-Basket Recommendation Algorithms

no code implementations7 Sep 2022 Zhufeng Shao, Shoujin Wang, Qian Zhang, Wenpeng Lu, Zhao Li, Xueping Peng

Different studies often evaluate NBR approaches on different datasets, under different experimental settings, making it hard to fairly and effectively compare the performance of different NBR approaches.

Next-basket recommendation Recommendation Systems

Re-weighting Negative Samples for Model-Agnostic Matching

no code implementations6 Jul 2022 Jiazhen Lou, Hong Wen, Fuyu Lv, Jing Zhang, Tengfei Yuan, Zhao Li

Recommender Systems (RS), as an efficient tool to discover users' interested items from a very large corpus, has attracted more and more attention from academia and industry.

Multi-Task Learning Recommendation Systems

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

1 code implementation15 Jun 2022 Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao Li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester

Motivated by the tremendous success of deep learning in clustering, one of the most fundamental machine learning tasks, and the large number of recent advances in this direction, in this paper we conduct a comprehensive survey on deep clustering by proposing a new taxonomy of different state-of-the-art approaches.

Clustering Deep Clustering +1

RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on

2 code implementations24 Apr 2022 Chao Lin, Zhao Li, Sheng Zhou, Shichang Hu, Jialun Zhang, Linhao Luo, Jiarun Zhang, Longtao Huang, Yuan He

Virtual try-on(VTON) aims at fitting target clothes to reference person images, which is widely adopted in e-commerce. Existing VTON approaches can be narrowly categorized into Parser-Based(PB) and Parser-Free(PF) by whether relying on the parser information to mask the persons' clothes and synthesize try-on images.

Virtual Try-on

Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump

1 code implementation21 Apr 2022 Sihao Hu, Zhen Zhang, Shengliang Lu, Bingsheng He, Zhao Li

With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors.

MAMDR: A Model Agnostic Learning Method for Multi-Domain Recommendation

1 code implementation25 Feb 2022 Linhao Luo, Yumeng Li, Buyu Gao, Shuai Tang, Sinan Wang, Jiancheng Li, Tanchao Zhu, Jiancai Liu, Zhao Li, Shirui Pan

We integrate these components into a unified framework and present MAMDR, which can be applied to any model structure to perform multi-domain recommendation.

Community Trend Prediction on Heterogeneous Graph in E-commerce

no code implementations24 Feb 2022 Jiahao Yuan, Zhao Li, Pengcheng Zou, Xuan Gao, Jinwei Pan, Wendi Ji, Xiaoling Wang

In online shopping, ever-changing fashion trends make merchants need to prepare more differentiated products to meet the diversified demands, and e-commerce platforms need to capture the market trend with a prophetic vision.


GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction

1 code implementation21 Feb 2022 Sihao Hu, Yi Cao, Yu Gong, Zhao Li, Yazheng Yang, Qingwen Liu, Shouling Ji

Specifically, we establish a heterogeneous graph that contains physical and semantic linkages to guide the feature transfer process from warmed-up video to cold-start videos.

Click-Through Rate Prediction

Deep Interest Highlight Network for Click-Through Rate Prediction in Trigger-Induced Recommendation

1 code implementation5 Feb 2022 Qijie Shen, Hong Wen, Wanjie Tao, Jing Zhang, Fuyu Lv, Zulong Chen, Zhao Li

In many classical e-commerce platforms, personalized recommendation has been proven to be of great business value, which can improve user satisfaction and increase the revenue of platforms.

Click-Through Rate Prediction

DBC-Forest: Deep forest with binning confidence screening

no code implementations25 Dec 2021 Pengfei Ma, Youxi Wu, Yan Li, Lei Guo, Zhao Li

As a deep learning model, deep confidence screening forest (gcForestcs) has achieved great success in various applications.

Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming

no code implementations20 Nov 2021 Yizhen Zheng, Ming Jin, Shirui Pan, Yuan-Fang Li, Hao Peng, Ming Li, Zhao Li

To overcome the aforementioned problems, we introduce a novel self-supervised graph representation learning algorithm via Graph Contrastive Adjusted Zooming, namely G-Zoom, to learn node representations by leveraging the proposed adjusted zooming scheme.

Contrastive Learning Graph Representation Learning +1

Adaptive Multi-receptive Field Spatial-Temporal Graph Convolutional Network for Traffic Forecasting

no code implementations1 Nov 2021 Xing Wang, Juan Zhao, Lin Zhu, Xu Zhou, Zhao Li, Junlan Feng, Chao Deng, Yong Zhang

AMF-STGCN extends GCN by (1) jointly modeling the complex spatial-temporal dependencies in mobile networks, (2) applying attention mechanisms to capture various Receptive Fields of heterogeneous base stations, and (3) introducing an extra decoder based on a fully connected deep network to conquer the error propagation challenge with multi-step forecasting.

Pre-trained Language Models in Biomedical Domain: A Systematic Survey

1 code implementation11 Oct 2021 Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Jie Fu

In this paper, we summarize the recent progress of pre-trained language models in the biomedical domain and their applications in biomedical downstream tasks.

Thompson Sampling for Unimodal Bandits

no code implementations15 Jun 2021 Long Yang, Zhao Li, Zehong Hu, Shasha Ruan, Shijian Li, Gang Pan, Hongyang Chen

In this paper, we propose a Thompson Sampling algorithm for \emph{unimodal} bandits, where the expected reward is unimodal over the partially ordered arms.

Thompson Sampling

Physical Artificial Intelligence: The Concept Expansion of Next-Generation Artificial Intelligence

no code implementations13 May 2021 Yingbo Li, Yucong Duan, Anamaria-Beatrice Spulber, Haoyang Che, Zakaria Maamar, Zhao Li, Chen Yang, Yu Lei

In this paper we explore the concept of Physicial Artifical Intelligence and propose two subdomains: Integrated Physicial Artifical Intelligence and Distributed Physicial Artifical Intelligence.

GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy

1 code implementation21 Apr 2021 Yongchao Liu, Houyi Li, Guowei Zhang, Xintan Zeng, Yongyong Li, Bin Huang, Peng Zhang, Zhao Li, Xiaowei Zhu, Changhua He, WenGuang Chen

Herein, we present GraphTheta, the first distributed and scalable graph learning system built upon vertex-centric distributed graph processing with neural network operators implemented as user-defined functions.

Graph Learning

Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning

1 code implementation27 Feb 2021 Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis

Our framework fully exploits the local information from network data by sampling a novel type of contrastive instance pair, which can capture the relationship between each node and its neighboring substructure in an unsupervised way.

Anomaly Detection Contrastive Learning +1

Reduction of planar double-box diagram for single-top production via auxiliary mass flow

no code implementations16 Feb 2021 Najam ul Basat, Zhao Li, Yefan Wang

The single-top production is an important process at the LHC to test the Standard Model (SM) and search for the new physics beyond the SM.

High Energy Physics - Phenomenology

Adaptive Spatial-Temporal Inception Graph Convolutional Networks for Multi-step Spatial-Temporal Network Data Forecasting

no code implementations1 Jan 2021 Xing Wang, Lin Zhu, Juan Zhao, Zhou Xu, Zhao Li, Junlan Feng, Chao Deng

Spatial-temporal data forecasting is of great importance for industries such as telecom network operation and transportation management.


Categorization of two-loop Feynman diagrams in the $\mathcal O(α^2)$ correction to $e^+e^- \rightarrow ZH$

1 code implementation23 Dec 2020 Zhao Li, Yefan Wang, Quan-feng Wu

The $e^+e^- \rightarrow ZH$ process is the dominant process for the Higgs boson production at the future Higgs factory.

High Energy Physics - Phenomenology

Cyclic Label Propagation for Graph Semi-supervised Learning

no code implementations24 Nov 2020 Zhao Li, Yixin Liu, Zhen Zhang, Shirui Pan, Jianliang Gao, Jiajun Bu

To overcome these limitations, we introduce a novel framework for graph semi-supervised learning termed as Cyclic Label Propagation (CycProp for abbreviation), which integrates GNNs into the process of label propagation in a cyclic and mutually reinforcing manner to exploit the advantages of both GNNs and LPA.

Node Classification

Distant Supervision for E-commerce Query Segmentation via Attention Network

no code implementations9 Nov 2020 Zhao Li, Donghui Ding, Pengcheng Zou, Yu Gong, Xi Chen, Ji Zhang, Jianliang Gao, Youxi Wu, Yucong Duan

The booming online e-commerce platforms demand highly accurate approaches to segment queries that carry the product requirements of consumers.


Unsupervised Cross-Lingual Adaptation of Dependency Parsers Using CRF Autoencoders

1 code implementation Findings of the Association for Computational Linguistics 2020 Zhao Li, Kewei Tu

We consider the task of cross-lingual adaptation of dependency parsers without annotated target corpora and parallel corpora.

Method and Dataset Entity Mining in Scientific Literature: A CNN + Bi-LSTM Model with Self-attention

no code implementations26 Oct 2020 Linlin Hou, Ji Zhang, Ou wu, Ting Yu, Zhen Wang, Zhao Li, Jianliang Gao, Yingchun Ye, Rujing Yao

We finally apply our model on PAKDD papers published from 2009-2019 to mine insightful results from scientific papers published in a longer time span.

Data Augmentation

Demon: Improved Neural Network Training with Momentum Decay

2 code implementations11 Oct 2019 John Chen, Cameron Wolfe, Zhao Li, Anastasios Kyrillidis

Momentum is a widely used technique for gradient-based optimizers in deep learning.

Image Classification

Cross-modal Zero-shot Hashing

no code implementations19 Aug 2019 Xuanwu Liu, Zhao Li, Jun Wang, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang

It then defines an objective function to achieve deep feature learning compatible with the composite similarity preserving, category attribute space learning, and hashing coding function learning.

Attribute Retrieval

ActiveHNE: Active Heterogeneous Network Embedding

no code implementations14 May 2019 Xia Chen, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang

To maximize the profit of utilizing the rare and valuable supervised information in HNEs, we develop a novel Active Heterogeneous Network Embedding (ActiveHNE) framework, which includes two components: Discriminative Heterogeneous Network Embedding (DHNE) and Active Query in Heterogeneous Networks (AQHN).

Network Embedding

Deep Multi-scale Discriminative Networks for Double JPEG Compression Forensics

no code implementations4 Apr 2019 Cheng Deng, Zhao Li, Xinbo Gao, DaCheng Tao

In this area, extracting effective statistical characteristics from a JPEG image for classification remains a challenge.

General Classification

Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce

no code implementations NAACL 2019 Jian-Guo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S. Yu

To address this discrepancy, previous studies mainly consider textual information of long product titles and lacks of human-like view during training and evaluation process.

Attribute Generative Adversarial Network

Personalized Bundle List Recommendation

no code implementations3 Apr 2019 Jinze Bai, Chang Zhou, Junshuai Song, Xiaoru Qu, Weiting An, Zhao Li, Jun Gao

In particular, BGN improves the precision of the best competitors by 16\% on average while maintaining the highest diversity on four datasets, and yields a 3. 85x improvement of response time over the best competitors in the bundle list recommendation problem.

Marketing Point Processes +1

Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction

no code implementations11 Sep 2018 Jian-Guo Zhang, Ji Wang, Lifang He, Zhao Li, Philip S. Yu

Then, it is possible to utilize unlabeled data that have a potential of failure to further improve the performance of the model.

Anomaly Detection Cloud Computing

Automatic Generation of Chinese Short Product Titles for Mobile Display

1 code implementation30 Mar 2018 Yu Gong, Xusheng Luo, Kenny Q. Zhu, Wenwu Ou, Zhao Li, Lu Duan

This paper studies the problem of automatically extracting a short title from a manually written longer description of E-commerce products for display on mobile devices.

Extractive Summarization

Tournament selection in zeroth-level classifier systems based on average reward reinforcement learning

no code implementations26 Apr 2016 Zhaoxiang Zang, Zhao Li, Junying Wang, Zhiping Dan

As a genetics-based machine learning technique, zeroth-level classifier system (ZCS) is based on a discounted reward reinforcement learning algorithm, bucket-brigade algorithm, which optimizes the discounted total reward received by an agent but is not suitable for all multi-step problems, especially large-size ones.

reinforcement-learning Reinforcement Learning (RL)

New parton distributions for collider physics

no code implementations14 Jul 2010 Hung-Liang Lai, Marco Guzzi, Joey Huston, Zhao Li, Pavel M. Nadolsky, Jon Pumplin, C. -P. Yuan

We extract new parton distribution functions (PDFs) of the proton by global analysis of hard scattering data in the general-mass framework of perturbative quantum chromodynamics.

High Energy Physics - Phenomenology

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