Saved in:
| Main Authors: | Maione, Francesco, Lino, Paolo, Giannino, Giuseppe, Maione, Guido |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.12733 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
$H$-convergence for equations depending on monotone operators in Carnot groups
by: Maione, Alberto
Published: (2019)
by: Maione, Alberto
Published: (2019)
Fractional Sobolev spaces via interpolation, and applications to mixed local-nonlocal operators
by: Maione, Alberto
Published: (2025)
by: Maione, Alberto
Published: (2025)
The automotive recall data search and its analysis applying machine learning
by: Bruno Fernandes Maione
Published: (2023)
by: Bruno Fernandes Maione
Published: (2023)
Catastrophic Failure of LLM Unlearning via Quantization
by: Zhang, Zhiwei, et al.
Published: (2024)
by: Zhang, Zhiwei, et al.
Published: (2024)
Ordem e Justiça na Sociedade Internacional pós-11 de Setembro
by: Emerson Maione de Souza
Published: (2009)
by: Emerson Maione de Souza
Published: (2009)
How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning
by: Serra, Giuseppe, et al.
Published: (2024)
by: Serra, Giuseppe, et al.
Published: (2024)
Interpretable Early Failure Detection via Machine Learning and Trace Checking-based Monitoring
by: Brunello, Andrea, et al.
Published: (2025)
by: Brunello, Andrea, et al.
Published: (2025)
Failure Detection in Chemical Processes Using Symbolic Machine Learning: A Case Study on Ethylene Oxidation
by: Amblard, Julien, et al.
Published: (2026)
by: Amblard, Julien, et al.
Published: (2026)
Early Detection of Coronary Heart Disease Using Hybrid Quantum Machine Learning Approach
by: Banday, Mehroush, et al.
Published: (2024)
by: Banday, Mehroush, et al.
Published: (2024)
Dependable Distributed Training of Compressed Machine Learning Models
by: Malandrino, Francesco, et al.
Published: (2024)
by: Malandrino, Francesco, et al.
Published: (2024)
Variational convergences under moving anisotropies
by: Maione, Alberto, et al.
Published: (2025)
by: Maione, Alberto, et al.
Published: (2025)
$H$-compactness for nonlocal linear operators in fractional divergence form
by: Caponi, Maicol, et al.
Published: (2024)
by: Caponi, Maicol, et al.
Published: (2024)
Remission of Acromegaly: The Sooner the Better
by: Thomas Cuny, et al.
Published: (2024)
by: Thomas Cuny, et al.
Published: (2024)
Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems
by: Banerjee, Sourasekhar, et al.
Published: (2026)
by: Banerjee, Sourasekhar, et al.
Published: (2026)
Artificial Intelligence-Enabled Spirometry for Early Detection of Right Heart Failure
by: Liu, Bin, et al.
Published: (2025)
by: Liu, Bin, et al.
Published: (2025)
Incorporating Failure of Machine Learning in Dynamic Probabilistic Safety Assurance
by: Arshadizadeh, Razieh, et al.
Published: (2025)
by: Arshadizadeh, Razieh, et al.
Published: (2025)
Sequencing to Mitigate Catastrophic Forgetting in Continual Learning
by: Moussa, Hesham G., et al.
Published: (2025)
by: Moussa, Hesham G., et al.
Published: (2025)
Avoiding Catastrophe in Online Learning by Asking for Help
by: Plaut, Benjamin, et al.
Published: (2024)
by: Plaut, Benjamin, et al.
Published: (2024)
Assessing the Feasibility of Early Cancer Detection Using Routine Laboratory Data: An Evaluation of Machine Learning Approaches on an Imbalanced Dataset
by: Li, Shumin
Published: (2025)
by: Li, Shumin
Published: (2025)
Enhancing the Detection of Coronary Artery Disease Using Machine Learning
by: Singh, Karan Kumar, et al.
Published: (2026)
by: Singh, Karan Kumar, et al.
Published: (2026)
Consequentialist Objectives and Catastrophe
by: Marklund, Henrik, et al.
Published: (2026)
by: Marklund, Henrik, et al.
Published: (2026)
Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies
by: Xu, Chen, et al.
Published: (2025)
by: Xu, Chen, et al.
Published: (2025)
Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning
by: Elsayed, Mohamed, et al.
Published: (2024)
by: Elsayed, Mohamed, et al.
Published: (2024)
On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
by: Peng, Ze, et al.
Published: (2025)
by: Peng, Ze, et al.
Published: (2025)
Early Risk Stratification of Dosing Errors in Clinical Trials Using Machine Learning
by: Hêche, Félicien, et al.
Published: (2026)
by: Hêche, Félicien, et al.
Published: (2026)
A new case of amyloid elastosis – dermoscopic findings and literature review
by: Luca Bettolini, et al.
Published: (2024)
by: Luca Bettolini, et al.
Published: (2024)
Leveraging Machine Learning for Early Detection of Lung Diseases
by: Rahmani, Bahareh, et al.
Published: (2025)
by: Rahmani, Bahareh, et al.
Published: (2025)
Leveraging Machine Learning for Early Autism Detection via INDT-ASD Indian Database
by: Shrivastava, Trapti, et al.
Published: (2024)
by: Shrivastava, Trapti, et al.
Published: (2024)
Phase field model for multi-material shape optimization of inextensible rods
by: Dondl, Patrick, et al.
Published: (2022)
by: Dondl, Patrick, et al.
Published: (2022)
Continual Learning and Catastrophic Forgetting
by: van de Ven, Gido M., et al.
Published: (2024)
by: van de Ven, Gido M., et al.
Published: (2024)
Stonefish: Supporting Machine Learning Research in Marine Robotics
by: Grimaldi, Michele, et al.
Published: (2025)
by: Grimaldi, Michele, et al.
Published: (2025)
Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning Environments
by: Gandhi, Atith, et al.
Published: (2024)
by: Gandhi, Atith, et al.
Published: (2024)
Leveraging Gene Expression Data and Explainable Machine Learning for Enhanced Early Detection of Type 2 Diabetes
by: Roy, Aurora Lithe, et al.
Published: (2024)
by: Roy, Aurora Lithe, et al.
Published: (2024)
MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
by: Carnelos, Matteo, et al.
Published: (2024)
by: Carnelos, Matteo, et al.
Published: (2024)
Early Detection of Pancreatic Cancer Using Multimodal Learning on Electronic Health Records
by: Aouad, Mosbah, et al.
Published: (2025)
by: Aouad, Mosbah, et al.
Published: (2025)
CORE: Mitigating Catastrophic Forgetting in Continual Learning through Cognitive Replay
by: Zhang, Jianshu, et al.
Published: (2024)
by: Zhang, Jianshu, et al.
Published: (2024)
Catastrophic Forgetting in Kolmogorov-Arnold Networks
by: Rahman, Mohammad Marufur, et al.
Published: (2025)
by: Rahman, Mohammad Marufur, et al.
Published: (2025)
Artificial Intelligence: Arguments for Catastrophic Risk
by: Bales, Adam, et al.
Published: (2024)
by: Bales, Adam, et al.
Published: (2024)
A Guide to Failure in Machine Learning: Reliability and Robustness from Foundations to Practice
by: Heim, Eric, et al.
Published: (2025)
by: Heim, Eric, et al.
Published: (2025)
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers
by: Kenneweg, Philip, et al.
Published: (2024)
by: Kenneweg, Philip, et al.
Published: (2024)
Similar Items
-
$H$-convergence for equations depending on monotone operators in Carnot groups
by: Maione, Alberto
Published: (2019) -
Fractional Sobolev spaces via interpolation, and applications to mixed local-nonlocal operators
by: Maione, Alberto
Published: (2025) -
The automotive recall data search and its analysis applying machine learning
by: Bruno Fernandes Maione
Published: (2023) -
Catastrophic Failure of LLM Unlearning via Quantization
by: Zhang, Zhiwei, et al.
Published: (2024) -
Ordem e Justiça na Sociedade Internacional pós-11 de Setembro
by: Emerson Maione de Souza
Published: (2009)