Wei Luo

Orcid: 0000-0002-4711-7543

Affiliations:
  • Deakin University, Geelong, VIC, Australia
  • Simon Fraser University, Vancouver-Burnaby, BC, Canada (PhD 2008)


According to our database1, Wei Luo authored at least 77 papers between 2005 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Distributed Optimization of Graph Convolutional Network Using Subgraph Variance.
IEEE Trans. Neural Networks Learn. Syst., August, 2024

Robust visual question answering via semantic cross modal augmentation.
Comput. Vis. Image Underst., January, 2024

Effective Individual Fairest Community Search over Heterogeneous Information Networks.
CoRR, 2024

Robust Backdoor Detection for Deep Learning via Topological Evolution Dynamics.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

ICPR 2024 Competition on Multi-line Mathematical Expressions Recognition.
Proceedings of the Pattern Recognition. Competitions - 27th International Conference, 2024

IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Beyond Linguistic Cues: Fine-grained Conversational Emotion Recognition via Belief-Desire Modelling.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
Robust federated learning under statistical heterogeneity via Hessian spectral decomposition.
Pattern Recognit., September, 2023

Robust federated learning under statistical heterogeneity via hessian-weighted aggregation.
Mach. Learn., February, 2023

Cyber Code Intelligence for Android Malware Detection.
IEEE Trans. Cybern., 2023

Federated Learning Under Statistical Heterogeneity on Riemannian Manifolds.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Embracing the dropouts in single-cell RNA-seq dynamics modelling.
Proceedings of the International Joint Conference on Neural Networks, 2023

Backdoor Attack on Deep Neural Networks in Perception Domain.
Proceedings of the International Joint Conference on Neural Networks, 2023

Bio-Inspired Dual-Network Model to Tackle Statistical Heterogeneity in Federated Learning.
Proceedings of the International Joint Conference on Neural Networks, 2023

Do We Need an Encoder-Decoder to Model Dynamical Systems on Networks?
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Tackling Model Mismatch with Mixup Regulated Test-Time Training.
Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

Learning Stable Task-Level Manifold for Few-Shot Learning.
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023

Robust quantification of prediction uncertainty by inducing heterogeneity in deep ensembles.
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023

Bridging the Interpretability Gap in Coupled Neural Dynamical Models.
Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

A Hessian-Based Federated Learning Approach to Tackle Statistical Heterogeneity.
Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

2022
A multiple feature fusion framework for video emotion recognition in the wild.
Concurr. Comput. Pract. Exp., 2022

Novel-domain Object Segmentation via Reliability-aware Teacher Ensemble.
Proceedings of the 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, 2022

Attention-based Feature Fusion for Reconstructing Gene-Regulatory Interactions.
Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

2021
Software Vulnerability Discovery via Learning Multi-Domain Knowledge Bases.
IEEE Trans. Dependable Secur. Comput., 2021

Con2Vec: Learning embedding representations for contrast sets.
Knowl. Based Syst., 2021

A Survey of Android Malware Detection with Deep Neural Models.
ACM Comput. Surv., 2021

Distributed Optimization of Graph Convolutional Network using Subgraph Variance.
CoRR, 2021

Ultra-short term wholesale electricity price forecasting through deep learning.
Proceedings of the 2021 IEEE PES Innovative Smart Grid Technologies, 2021

Impute Gene Expression Missing Values via Biological Networks: Optimal Fusion of Data and Knowledge.
Proceedings of the International Joint Conference on Neural Networks, 2021

Microwave Link Failures Prediction via LSTM-based Feature Fusion Network.
Proceedings of the International Joint Conference on Neural Networks, 2021

Robust Neural Regression via Uncertainty Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
MODEL: Motif-Based Deep Feature Learning for Link Prediction.
IEEE Trans. Comput. Soc. Syst., 2020

Gathering Intelligence on Student Information Behavior Using Data Mining.
Libr. Trends, 2020

Succinct contrast sets via false positive controlling with an application in clinical process redesign.
Expert Syst. Appl., 2020

Machine Learning for Financial Risk Management: A Survey.
IEEE Access, 2020

Bias-regularised Neural-Network Metamodelling of Insurance Portfolio Risk.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data.
Sensors, 2019

Modelling Match Outcome in Australian Football: Improved accuracy with large databases.
Int. J. Comput. Sci. Sport, 2019

A3CM: Automatic Capability Annotation for Android Malware.
IEEE Access, 2019

Predicting the Impact of Android Malicious Samples via Machine Learning.
IEEE Access, 2019

Fast Valuation of Large Portfolios of Variable Annuities via Transfer Learning.
Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

Data-Driven Android Malware Intelligence: A Survey.
Proceedings of the Machine Learning for Cyber Security - Second International Conference, 2019

Deep Neighbor Embedding for Evaluation of Large Portfolios of Variable Annuities.
Proceedings of the Knowledge Science, Engineering and Management, 2019

A Novel Video Emotion Recognition System in the Wild Using a Random Forest Classifier.
Proceedings of the Data Science - 6th International Conference, 2019

Robust Anomaly Detection in Videos Using Multilevel Representations.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Cross-Project Transfer Representation Learning for Vulnerable Function Discovery.
IEEE Trans. Ind. Informatics, 2018

LTARM: A novel temporal association rule mining method to understand toxicities in a routine cancer treatment.
Knowl. Based Syst., 2018

Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding.
J. Medical Syst., 2018

Learning Graph Representation via Frequent Subgraphs.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Keep Calm and Know Where to Focus: Measuring and Predicting the Impact of Android Malware.
Proceedings of the Advanced Data Mining and Applications - 14th International Conference, 2018

Batch Normalized Deep Boltzmann Machines.
Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017
POSTER: Vulnerability Discovery with Function Representation Learning from Unlabeled Projects.
Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017

2016
Control Matching via Discharge Code Sequences.
CoRR, 2016

Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data.
Proceedings of the 1st Machine Learning in Health Care, 2016

Forecasting Patient Outflow from Wards having No Real-Time Clinical Data.
Proceedings of the 2016 IEEE International Conference on Healthcare Informatics, 2016

Exceptional Contrast Set Mining: Moving Beyond the Deluge of the Obvious.
Proceedings of the AI 2016: Advances in Artificial Intelligence, 2016

2015
Stabilized sparse ordinal regression for medical risk stratification.
Knowl. Inf. Syst., 2015

Robust Traffic Classification with Mislabelled Training Samples.
Proceedings of the 21st IEEE International Conference on Parallel and Distributed Systems, 2015

Understanding Toxicities and Complications of Cancer Treatment: A Data Mining Approach.
Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015

2014
A framework for feature extraction from hospital medical data with applications in risk prediction.
BMC Bioinform., 2014

Detecting contaminated birthdates using generalized additive models.
BMC Bioinform., 2014

iPoll: Automatic Polling Using Online Search.
Proceedings of the Web Information Systems Engineering - WISE 2014, 2014

Unsupervised inference of significant locations from WiFi data for understanding human dynamics.
Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia, 2014

Individualized arrhythmia detection with ECG signals from wearable devices.
Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013
Parameter-Free Search of Time-Series Discord.
J. Comput. Sci. Technol., 2013

An integrated framework for suicide risk prediction.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2011
Faster and Parameter-Free Discord Search in Quasi-Periodic Time Series.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

2010
Mind change optimal learning of Bayes net structure from dependency and independency data.
Inf. Comput., 2010

Unsupervised DRG Upcoding Detection in Healthcare Databases.
Proceedings of the ICDMW 2010, 2010

2009
A new hybrid method for Bayesian network learning With dependency constraints.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2009

2007
Mind Change Optimal Learning of Bayes Net Structure.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Mind change efficient learning.
Inf. Comput., 2006

Learning Bayesian Networks in Semi-deterministic Systems.
Proceedings of the Advances in Artificial Intelligence, 2006

2005
Compute Inclusion Depth of a Pattern.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005


  Loading...