Wei Zhu

Orcid: 0000-0002-3811-8261

Affiliations:
  • University of Rochester, Department of Computer Science, NY, USA
  • Northwestern Polytechnical University, Center for OPTical IMagery Analysis and Learning (OPTIMAL), Xi'an, China (former)


According to our database1, Wei Zhu authored at least 24 papers between 2016 and 2024.

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

Timeline

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Bibliography

2024
Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023
Unsupervised anomaly detection by densely contrastive learning for time series data.
Neural Networks, November, 2023

SegPrompt: Using Segmentation Map as a Better Prompt to Finetune Deep Models for Kidney Stone Classification.
CoRR, 2023

SegPrompt: Using Segmentation Map as a Better Prompt to Finetune Deep Models for Kidney Stone Classification.
Proceedings of the Medical Imaging with Deep Learning, 2023

Remote Medication Status Prediction for Individuals with Parkinson's Disease using Time-series Data from Smartphones.
Proceedings of the IEEE International Conference on Digital Health, 2023

2022
Unsupervised Large Graph Embedding Based on Balanced and Hierarchical K-Means.
IEEE Trans. Knowl. Data Eng., 2022

Federated learning of molecular properties with graph neural networks in a heterogeneous setting.
Patterns, 2022

Federated Medical Image Analysis with Virtual Sample Synthesis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Localized Adversarial Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Deep Federated Anomaly Detection for Multivariate Time Series Data.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Structured Graph Optimization for Unsupervised Feature Selection.
IEEE Trans. Knowl. Data Eng., 2021

Temperature network for few-shot learning with distribution-aware large-margin metric.
Pattern Recognit., 2021

Federated Learning of Molecular Properties in a Heterogeneous Setting.
CoRR, 2021

Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Decision Tree SVM: An extension of linear SVM for non-linear classification.
Neurocomputing, 2020

Unifying Specialist Image Embedding into Universal Image Embedding.
CoRR, 2020

Alleviating the Incompatibility Between Cross Entropy Loss and Episode Training for Few-Shot Skin Disease Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Modeling Heterogeneity in Feature Selection for MCI Classification.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2017
Fast Spectral Clustering with efficient large graph construction.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Unsupervised Large Graph Embedding.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Unsupervised Feature Selection with Structured Graph Optimization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016


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