Sheng Zhou

Orcid: 0000-0003-3645-1041

Affiliations:
  • Zhejiang University, Ningbo Research Institute, School of Software Technology, China
  • Zhejiang University, Alibaba, Joint Institute of Frontier Technologies, China


According to our database1, Sheng Zhou authored at least 65 papers between 2018 and 2024.

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Bibliography

2024
Online adversarial knowledge distillation for graph neural networks.
Expert Syst. Appl., March, 2024

Structure enhanced prototypical alignment for unsupervised cross-domain node classification.
Neural Networks, 2024

AdaDFKD: Exploring adaptive inter-sample relationship in data-free knowledge distillation.
Neural Networks, 2024

Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding.
CoRR, 2024

Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation.
CoRR, 2024

GC-Bench: An Open and Unified Benchmark for Graph Condensation.
CoRR, 2024

MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction.
CoRR, 2024

Motif-driven Subgraph Structure Learning for Graph Classification.
CoRR, 2024

Better Late Than Never: Formulating and Benchmarking Recommendation Editing.
CoRR, 2024

NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise.
CoRR, 2024

Towards a Unified Framework of Clustering-based Anomaly Detection.
CoRR, 2024

Heterophilous Distribution Propagation for Graph Neural Networks.
CoRR, 2024

Revisiting the Message Passing in Heterophilous Graph Neural Networks.
CoRR, 2024

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection.
CoRR, 2024

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective.
CoRR, 2024

A Survey on Graph Condensation.
CoRR, 2024

Distributionally Robust Graph-based Recommendation System.
Proceedings of the ACM on Web Conference 2024, 2024

Macro Graph Neural Networks for Online Billion-Scale Recommender Systems.
Proceedings of the ACM on Web Conference 2024, 2024

SIGformer: Sign-aware Graph Transformer for Recommendation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Inversive-Reasoning Augmentation for Natural Language Inference.
Proceedings of the IEEE International Conference on Acoustics, 2024

MMAD: Multi-modal Movie Audio Description.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Rethinking Propagation for Unsupervised Graph Domain Adaptation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation.
IEEE Trans. Knowl. Data Eng., October, 2023

Hierarchical Knowledge Propagation and Distillation for Few-Shot Learning.
Neural Networks, October, 2023

Source-free semi-supervised domain adaptation via progressive Mixup.
Knowl. Based Syst., February, 2023

SamWalker++: Recommendation With Informative Sampling Strategy.
IEEE Trans. Knowl. Data Eng., 2023

Dynamic data-free knowledge distillation by easy-to-hard learning strategy.
Inf. Sci., 2023

Improving topic disentanglement via contrastive learning.
Inf. Process. Manag., 2023

Modeling Spatiotemporal Periodicity and Collaborative Signal for Local-Life Service Recommendation.
CoRR, 2023

Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR.
CoRR, 2023

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation.
CoRR, 2023

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Unbiased Knowledge Distillation for Recommendation.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection.
Proceedings of the IEEE International Conference on Data Mining, 2023

Zero-Shot Entity Typing in Knowledge Graphs.
Proceedings of the Database Systems for Advanced Applications. DASFAA 2023 International Workshops, 2023

DPGN: Denoising Periodic Graph Network for Life Service Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

CDR: Conservative Doubly Robust Learning for Debiased Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Homophily-enhanced Structure Learning for Graph Clustering.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Robust Sequence Networked Submodular Maximization.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Direction-Aware User Recommendation Based on Asymmetric Network Embedding.
ACM Trans. Inf. Syst., 2022

Context-guided entropy minimization for semi-supervised domain adaptation.
Neural Networks, 2022

How to Teach: Learning Data-Free Knowledge Distillation from Curriculum.
CoRR, 2022

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions.
CoRR, 2022

Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Hilbert Distillation for Cross-Dimensionality Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Spatial-Preserved Skeleton Representations for Few-Shot Action Recognition.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation.
ACM Trans. Inf. Syst., 2021

Efficient Medical Image Segmentation Based on Knowledge Distillation.
IEEE Trans. Medical Imaging, 2021

Profit maximization for competitive social advertising.
Theor. Comput. Sci., 2021

Online Adversarial Distillation for Graph Neural Networks.
CoRR, 2021

Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation.
CoRR, 2021

Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data.
CoRR, 2021

Distilling Holistic Knowledge with Graph Neural Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Cross Multi-Type Objects Clustering in Attributed Heterogeneous Information Network.
Knowl. Based Syst., 2020

Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

DGE: Deep Generative Network Embedding Based on Commonality and Individuality.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding.
CoRR, 2019

SamWalker: Social Recommendation with Informative Sampling Strategy.
Proceedings of the World Wide Web Conference, 2019

2018
ANRL: Attributed Network Representation Learning via Deep Neural Networks.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

PRRE: Personalized Relation Ranking Embedding for Attributed Networks.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Modeling Users' Exposure with Social Knowledge Influence and Consumption Influence for Recommendation.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018


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