Kai Zhao

Orcid: 0000-0002-5159-2312

Affiliations:
  • Aalborg University, Denmark
  • Beijing University of Posts and Telecommunications, China (former)


According to our database1, Kai Zhao authored at least 13 papers between 2020 and 2024.

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

Timeline

2020
2021
2022
2023
2024
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1
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3
4
5
4
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1
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3

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning.
CoRR, 2024

MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast.
CoRR, 2024

ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning.
CoRR, 2024

Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders.
CoRR, 2024

2023
Multiple Time Series Forecasting with Dynamic Graph Modeling.
Proc. VLDB Endow., December, 2023

Weakly Guided Adaptation for Robust Time Series Forecasting.
Proc. VLDB Endow., December, 2023

2022
A Pattern Discovery Approach to Multivariate Time Series Forecasting.
CoRR, 2022

Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

2021
Multiplex Network Embedding Model with High-Order Node Dependence.
Complex., 2021

Disentangled-based Adversarial Network for Multiplex Network Embedding.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Deep Adversarial Completion for Sparse Heterogeneous Information Network Embedding.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Tweet Stance Detection: A Two-stage DC-BILSTM Model Based on Semantic Attention.
Proceedings of the 5th IEEE International Conference on Data Science in Cyberspace, 2020

KGWD: Knowledge Graph Based Wide & Deep Framework for Recommendation.
Proceedings of the Web and Big Data - 4th International Joint Conference, 2020


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