no code implementations • 5 Jun 2024 • Yang Liu, Chuan Zhou, Peng Zhang, Shirui Pan, Zhao Li, Hongyang Chen
In recent years, there has been notable interest in investigating combinatorial optimization (CO) problems by neural-based framework.
1 code implementation • 5 Jun 2024 • Yang Liu, Peng Zhang, Yang Gao, Chuan Zhou, Zhao Li, Hongyang Chen
The idea of AutoGNP is to use graph neural architecture search algorithms to automatically find the best GNNs for a given NP-hard combinatorial optimization problem.
1 code implementation • 3 Mar 2024 • Zhen Zhang, Meihan Liu, Anhui Wang, Hongyang Chen, Zhao Li, Jiajun Bu, Bingsheng He
Unsupervised Graph Domain Adaptation (UGDA) has emerged as a practical solution to transfer knowledge from a label-rich source graph to a completely unlabelled target graph.
no code implementations • 14 Feb 2024 • Zhao Li, Xin Wang, Jun Zhao, Wenbin Guo, JianXin Li
It is desirable and challenging for knowledge hypergraph embedding to reach a trade-off between model effectiveness and efficiency.
no code implementations • 11 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.
no code implementations • 9 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).
no code implementations • 5 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.
no code implementations • 6 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.
no code implementations • 20 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.
no code implementations • 16 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.
1 code implementation • 19 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.
Ranked #1 on Node Property Prediction on ogbn-proteins
no code implementations • 29 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]".
Ranked #1 on Domain Generalization on VLCS
no code implementations • 17 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.
no code implementations • 7 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.
no code implementations • 7 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.
1 code implementation • 10 Aug 2022 • Jingsong Lv, Zhao Li, Hongyang Chen, Yao Qi, Chunqi Wu
In this paper, we propose a Path-aware Siamese Graph neural network(PSG) for link prediction tasks.
Ranked #1 on Link Property Prediction on ogbl-ddi
no code implementations • 6 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.
1 code implementation • 15 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.
2 code implementations • 24 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.
1 code implementation • 21 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.
no code implementations • 25 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.
no code implementations • 24 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.
1 code implementation • 21 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.
1 code implementation • 5 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.
1 code implementation • ACM Transactions on Knowledge Discovery from Data 2022 • Jianliang Gao, Xiaoting Ying, Cong Xu, Jianxin Wang, Shichao Zhang, Zhao Li
For a given group of stocks, the proposed TRAN model can output the ranking results of stocks according to their return ratios.
no code implementations • 25 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.
1 code implementation • Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval 2021 • Jiamin Chen, Jianliang Gao, Yibo Chen, Oloulade Babatounde Moctard, Tengfei Lyu, Zhao Li
In this paper, we propose a parallel graph architecture search (GraphPAS) framework for graph neural networks.
no code implementations • 20 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.
no code implementations • 1 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.
1 code implementation • 11 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.
no code implementations • 15 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.
no code implementations • 13 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.
1 code implementation • 21 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.
no code implementations • 27 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.
no code implementations • 16 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
no code implementations • 1 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.
1 code implementation • 23 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
no code implementations • 24 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.
no code implementations • 9 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.
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.
no code implementations • 26 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.
no code implementations • 6 Oct 2020 • Yuqi Si, Jingcheng Du, Zhao Li, Xiaoqian Jiang, Timothy Miller, Fei Wang, W. Jim Zheng, Kirk Roberts
We show the importance and feasibility of learning comprehensive representations of patient EHR data through a systematic review.
2 code implementations • 11 Oct 2019 • John Chen, Cameron Wolfe, Zhao Li, Anastasios Kyrillidis
Momentum is a widely used technique for gradient-based optimizers in deep learning.
no code implementations • 19 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.
no code implementations • 14 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).
no code implementations • 4 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.
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.
no code implementations • 3 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.
no code implementations • 11 Nov 2018 • Jian-Guo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Ye Liu, Xiuming Pan, Yu Gong, Philip S. Yu
Nowadays, an increasing number of customers are in favor of using E-commerce Apps to browse and purchase products.
no code implementations • 11 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.
1 code implementation • 30 Mar 2018 • Yu Gong, Xusheng Luo, Yu Zhu, Wenwu Ou, Zhao Li, Muhua Zhu, Kenny Q. Zhu, Lu Duan, Xi Chen
Slot filling is a critical task in natural language understanding (NLU) for dialog systems.
1 code implementation • 30 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.
no code implementations • 26 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.
no code implementations • 14 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