Cover Image

Towards an active-learning approach to resource allocation for population-based damage prognosis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tsialiamanis, George, Worden, Keith, Dervilis, Nikolaos, Hughes, Aidan J
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the topology and geometry of population-based SHM
by: Worden, Keith, et al.
Published: (2024)

Towards a population-informed approach to the definition of data-driven models for structural dynamics
by: Tsialiamanis, G., et al.
Published: (2023)

Cost-informed dimensionality reduction for structural digital twin technologies
by: Hughes, Aidan J., et al.
Published: (2024)

Quantifying the value of positive transfer: An experimental case study
by: Hughes, Aidan J., et al.
Published: (2024)

Active learning for regression in engineering populations: A risk-informed approach
by: Clarkson, Daniel R., et al.
Published: (2024)

Regularising NARX models with multi-task learning
by: Bee, Sarah, et al.
Published: (2025)

Multitask learning for improved scour detection: A dynamic wave tank study
by: Brealy, Simon M., et al.
Published: (2024)

When does a bridge become an aeroplane?
by: Dardeno, Tina A., et al.
Published: (2024)

Transfer learning via interpolating structures
by: Dardeno, T. A., et al.
Published: (2026)

Active transfer learning for structural health monitoring
by: Poole, J., et al.
Published: (2025)

Inter-turbine Modelling of Wind-Farm Power using Multi-task Learning
by: Brealy, Simon M., et al.
Published: (2025)

Physics-informed transfer learning for SHM via feature selection
by: Poole, J., et al.
Published: (2025)

On the use of Statistical Learning Theory for model selection in Structural Health Monitoring
by: Lindley, C. A., et al.
Published: (2025)

On Additive Gaussian Processes for Wind Farm Power Prediction
by: Brealy, Simon M., et al.
Published: (2026)

Anomaly Detection in Offshore Wind Turbine Structures using Hierarchical Bayesian Modelling
by: Smith, S. M., et al.
Published: (2024)

Multi-Task Equation Discovery
by: Bee, S C, et al.
Published: (2025)

On the hierarchical Bayesian modelling of frequency response functions
by: Dardeno, T. A., et al.
Published: (2023)

On the Detection and Quantification of Nonlinearity via Statistics of the Gradients of a Black-Box Model
by: Tsialiamanis, G., et al.
Published: (2023)

Canonical-Correlation-Based Fast Feature Selection for Structural Health Monitoring
by: Zhang, Sikai, et al.
Published: (2021)

Decision-centric fairness: Evaluation and optimization for resource allocation problems
by: De Vos, Simon, et al.
Published: (2025)

An active learning approach for improving the performance of equilibrium based chemical simulations
by: Savino, Mary, et al.
Published: (2021)

Predicting the activity of chemical compounds based on machine learning approaches
by: Tu, Do Hoang, et al.
Published: (2023)

Using machine learning for fault detection in lighthouse light sensors
by: Kampouridis, Michael, et al.
Published: (2024)

The impact of allocation strategies in subset learning on the expressive power of neural networks
by: Schlisselberg, Ofir, et al.
Published: (2025)

Toward efficient resource utilization at edge nodes in federated learning
by: Alawadi, Sadi, et al.
Published: (2023)

Privacy amplification by random allocation
by: Feldman, Vitaly, et al.
Published: (2025)

Deep learning architectures for data-driven damage detection in nonlinear dynamic systems
by: Joseph, Harrish, et al.
Published: (2024)

Version age-based client scheduling policy for federated learning
by: Hu, Xinyi, et al.
Published: (2024)

Engineering Microbial Symbiosis for Mars Habitability
by: Correll, Randall R., et al.
Published: (2025)

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
by: Raposo, David, et al.
Published: (2024)

Towards efficient compression and communication for prototype-based decentralized learning
by: Fernández-Piñeiro, Pablo, et al.
Published: (2024)

Universal Laboratory Model: prognosis of abnormal clinical outcomes based on routine tests
by: Karpov, Pavel, et al.
Published: (2025)

DeepAtlas: a tool for effective manifold learning
by: Hughes, Serena, et al.
Published: (2025)

Active partitioning: inverting the paradigm of active learning
by: Tacke, Marius, et al.
Published: (2024)

Estimating properties of a homogeneous bounded soil using machine learning models
by: Kalimeris, Konstantinos, et al.
Published: (2025)

Efficient privacy loss accounting for subsampling and random allocation
by: Feldman, Vitaly, et al.
Published: (2026)

An end-to-end attention-based approach for learning on graphs
by: Buterez, David, et al.
Published: (2024)

REDUCR: Robust Data Downsampling Using Class Priority Reweighting
by: Bankes, William, et al.
Published: (2023)

Stochastic parameter reduced-order model based on hybrid machine learning approaches
by: Fang, Cheng, et al.
Published: (2024)

Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty
by: George, Thomas, et al.
Published: (2022)