Wenyu Zhang

Orcid: 0000-0002-3849-4320

Affiliations:
  • Institute for Infocomm Research, Singapore
  • Cornell University, Ithaca, NY, USA (former)
  • Institute for Infocomm Research, Singapore (former)


According to our database1, Wenyu Zhang authored at least 26 papers between 2015 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Training neural networks with classification rules for incorporating domain knowledge.
Knowl. Based Syst., 2024

Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation.
CoRR, 2024

Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training.
CoRR, 2024

Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series.
IEEE Trans. Neural Networks Learn. Syst., 2022

Conditional Contrastive Domain Generalization for Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2022

Co-Learning with Pre-Trained Networks Improves Source-Free Domain Adaptation.
CoRR, 2022

Few-Shot Adaptation of Pre-Trained Networks for Domain Shift.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Domain Generalization via Selective Consistency Regularization for Time Series Classification.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021
AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series.
Data Min. Knowl. Discov., 2021

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series.
CoRR, 2021

HALO: Learning to Prune Neural Networks with Shrinkage.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

POLA: Online Time Series Prediction by Adaptive Learning Rates.
Proceedings of the IEEE International Conference on Acoustics, 2021

Robust Domain-Free Domain Generalization with Class-Aware Alignment.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Hierarchical Adaptive Lasso: Learning Sparse Neural Networks with Shrinkage via Single Stage Training.
CoRR, 2020

Multi-label Prediction in Time Series Data using Deep Neural Networks.
CoRR, 2020

CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learning Periods from Incomplete Multivariate Time Series.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

2017
Heterogeneous Sensor Data Fusion By Deep Multimodal Encoding.
IEEE J. Sel. Top. Signal Process., 2017

Pruning and Nonparametric Multiple Change Point Detection.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Deep fusion of heterogeneous sensor data.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2015
Multivariate Time Series Classification Using Dynamic Time Warping Template Selection for Human Activity Recognition.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Multimodal fusion for sensor data using stacked autoencoders.
Proceedings of the Tenth IEEE International Conference on Intelligent Sensors, 2015

Adaptive duty cycling in sensor networks via Continuous Time Markov Chain modelling.
Proceedings of the 2015 IEEE International Conference on Communications, 2015


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