A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design.
IEEE Trans. Neural Networks Learn. Syst., 2023
A Spiking Neural Network with Resistively Coupled Synapses Using Time-to-First-Spike Coding Towards Efficient Charge-Domain Computing.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022
Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time.
CoRR, 2020
Multi-view Learning over Retinal Thickness and Visual Sensitivity on Glaucomatous Eyes.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
System identification and parameter estimation in mathematical medicine: examples demonstrated for prostate cancer.
Quant. Biol., 2016
Predicting Glaucoma Visual Field Loss by Hierarchically Aggregating Clustering-based Predictors.
CoRR, 2016
Temporal Network Change Detection Using Network Centralities.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016
Predicting Glaucomatous Progression with Piecewise Regression Model from Heterogeneous Medical Data.
Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016), 2016
Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015
Predicting glaucoma progression using multi-task learning with heterogeneous features.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014