Dawei Zhou

Orcid: 0000-0002-3611-4363

Affiliations:
  • Virginia Tech, VA, USA
  • University of Illinois at Urbana-Champaign, IL, USA (former)
  • Arizona State University, Tempe, Arizona, USA (former)
  • University of Rochester, Rochester, NY, USA (former)


According to our database1, Dawei Zhou authored at least 38 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Rare Category Analysis for Complex Data: A Review.
ACM Comput. Surv., May, 2024

CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation.
CoRR, 2024

2023
HeroLT: Benchmarking Heterogeneous Long-Tailed Learning.
CoRR, 2023

GPatcher: A Simple and Adaptive MLP Model for Alleviating Graph Heterophily.
CoRR, 2023

Characterizing Long-Tail Categories on Graphs.
CoRR, 2023

Dynamic Transfer Learning across Graphs.
CoRR, 2023

FairGen: Towards Fair Graph Generation.
CoRR, 2023

Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs.
Proceedings of the ACM Web Conference 2023, 2023

Towards Reliable Rare Category Analysis on Graphs via Individual Calibration.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Personalized Federated Learning under Mixture of Distributions.
Proceedings of the International Conference on Machine Learning, 2023

TGEditor: Task-Guided Graph Editing for Augmenting Temporal Financial Transaction Networks.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Towards Bi-Level Out-of-Distribution Logical Reasoning on Knowledge Graphs.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
iNet: visual analysis of irregular transition in multivariate dynamic networks.
Frontiers Comput. Sci., 2022

Towards High-Order Complementary Recommendation via Logical Reasoning Network.
Proceedings of the IEEE International Conference on Data Mining, 2022

Augmenting Knowledge Transfer across Graphs.
Proceedings of the IEEE International Conference on Data Mining, 2022

MentorGNN: Deriving Curriculum for Pre-Training GNNs.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

TrustLOG: The First Workshop on Trustworthy Learning on Graphs.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
High-Order Structure Exploration on Massive Graphs: A Local Graph Clustering Perspective.
ACM Trans. Knowl. Discov. Data, 2021

2020
RCAnalyzer: visual analytics of rare categories in dynamic networks.
Frontiers Inf. Technol. Electron. Eng., 2020

Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

A Data-Driven Graph Generative Model for Temporal Interaction Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Local Motif Clustering on Time-Evolving Graphs.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

CANON: Complex Analytics of Network of Networks for Modeling Adversarial Activities.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Misc-GAN: A Multi-scale Generative Model for Graphs.
Frontiers Big Data, 2019

Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018
SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Motif-Preserving Dynamic Local Graph Cut.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Discovering rare categories from graph streams.
Data Min. Knowl. Discov., 2017

HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

A Local Algorithm for Structure-Preserving Graph Cut.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016
Jointly Modeling Label and Feature Heterogeneity in Medical Informatics.
ACM Trans. Knowl. Discov. Data, 2016

Bi-Level Rare Temporal Pattern Detection.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
REACH<sup>2</sup>-Mote: A Range-Extending Passive Wake-Up Wireless Sensor Node.
ACM Trans. Sens. Networks, 2015

MUVIR: Multi-View Rare Category Detection.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Rare Category Detection on Time-Evolving Graphs.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Tackling Mental Health by Integrating Unobtrusive Multimodal Sensing.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015


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