Raed Kontar

Orcid: 0000-0002-4546-324X

According to our database1, Raed Kontar authored at least 46 papers between 2017 and 2024.

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Bibliography

2024
SALR: Sharpness-Aware Learning Rate Scheduler for Improved Generalization.
IEEE Trans. Neural Networks Learn. Syst., September, 2024

Fed-ensemble: Ensemble Models in Federated Learning for Improved Generalization and Uncertainty Quantification.
IEEE Trans Autom. Sci. Eng., July, 2024

Federated Gaussian Process: Convergence, Automatic Personalization and Multi-Fidelity Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2024

Federated Condition Monitoring Signal Prediction With Improved Generalization.
IEEE Trans. Reliab., March, 2024

Federated Multi-Output Gaussian Processes.
Technometrics, 2024

Personalized PCA: Decoupling Shared and Unique Features.
J. Mach. Learn. Res., 2024

The Traveling Bandit: A Framework for Bayesian Optimization with Movement Costs.
CoRR, 2024

FCOM: A Federated Collaborative Online Monitoring Framework via Representation Learning.
CoRR, 2024

Triple Component Matrix Factorization: Untangling Global, Local, and Noisy Components.
CoRR, 2024

Real-time Adaptation for Condition Monitoring Signal Prediction using Label-aware Neural Processes.
CoRR, 2024

Intelligent Feedrate Optimization Using an Uncertainty-Aware Digital Twin Within a Model Predictive Control Framework.
IEEE Access, 2024

2023
Personalized Federated Learning via Domain Adaptation with an Application to Distributed 3D Printing.
Technometrics, July, 2023

SEE-OoD: Supervised Exploration For Enhanced Out-of-Distribution Detection.
CoRR, 2023

Personalized Tucker Decomposition: Modeling Commonality and Peculiarity on Tensor Data.
CoRR, 2023

Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design.
CoRR, 2023

Personalized Dictionary Learning for Heterogeneous Datasets.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
On Negative Transfer and Structure of Latent Functions in Multioutput Gaussian Processes.
SIAM/ASA J. Uncertain. Quantification, December, 2022

A Multi-Stage Approach for Knowledge-Guided Predictions With Application to Additive Manufacturing.
IEEE Trans Autom. Sci. Eng., 2022

Author Correction: Performance evaluation of a prescription medication image classification model: an observational cohort.
npj Digit. Medicine, 2022

Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits.
J. Mach. Learn. Res., 2022

Rethinking Cost-sensitive Classification in Deep Learning via Adversarial Data Augmentation.
CoRR, 2022

Federated Data Analytics: A Study on Linear Models.
CoRR, 2022

A Continual Learning Framework for Adaptive Defect Classification and Inspection.
CoRR, 2022

2021
Functional Principal Component Analysis for Extrapolating Multistream Longitudinal Data.
IEEE Trans. Reliab., 2021

Joint Models for Event Prediction From Time Series and Survival Data.
Technometrics, 2021

Minimizing Negative Transfer of Knowledge in Multivariate Gaussian Processes: A Scalable and Regularized Approach.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Performance evaluation of a prescription medication image classification model: an observational cohort.
npj Digit. Medicine, 2021

Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits.
CoRR, 2021

The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning.
CoRR, 2021

GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning.
CoRR, 2021

Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning.
CoRR, 2021

The Internet of Federated Things (IoFT).
IEEE Access, 2021

2020
Remaining useful life prediction based on degradation signals using monotonic B-splines with infinite support.
IISE Trans., 2020

SALR: Sharpness-aware Learning Rates for Improved Generalization.
CoRR, 2020

On Negative Transfer and Structure of Latent Functions in Multi-output Gaussian Processes.
CoRR, 2020

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes.
CoRR, 2020

Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Lookahead Bayesian Optimization via Rollout: Guarantees and Sequential Rolling Horizons.
CoRR, 2019

The Rényi Gaussian Process.
CoRR, 2019

Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data.
CoRR, 2019

Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes.
CoRR, 2019

2018
Nonparametric-Condition-Based Remaining Useful Life Prediction Incorporating External Factors.
IEEE Trans. Reliab., 2018

Nonparametric Modeling and Prognosis of Condition Monitoring Signals Using Multivariate Gaussian Convolution Processes.
Technometrics, 2018

Statistical monitoring of multiple profiles simultaneously using Gaussian processes.
Qual. Reliab. Eng. Int., 2018

2017
Estimation and monitoring of key performance indicators of manufacturing systems using the multi-output Gaussian process.
Int. J. Prod. Res., 2017


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