Saved in:
| Main Authors: | Caron, Emmanuel, Chretien, Stephane |
|---|---|
| Format: | Preprint |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2007.12882 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Detecting malignant dynamics on very few blood sample using signature coefficients
by: Vaucher, Rémi, et al.
Published: (2025)
by: Vaucher, Rémi, et al.
Published: (2025)
Time topological analysis of EEG using signature theory
by: Chrétien, Stéphane, et al.
Published: (2024)
by: Chrétien, Stéphane, et al.
Published: (2024)
Conformal Online Learning of Deep Koopman Linear Embeddings
by: Gao, Ben, et al.
Published: (2025)
by: Gao, Ben, et al.
Published: (2025)
Be aware of overfitting by hyperparameter optimization!
by: Tetko, Igor V., et al.
Published: (2024)
by: Tetko, Igor V., et al.
Published: (2024)
Understanding overfitting in random forest for probability estimation: a visualization and simulation study
by: Barreñada, Lasai, et al.
Published: (2024)
by: Barreñada, Lasai, et al.
Published: (2024)
Data-driven transport modelling without overfit
by: Vanya, Peter, et al.
Published: (2026)
by: Vanya, Peter, et al.
Published: (2026)
On robust overfitting: adversarial training induced distribution matters
by: Tian, Runzhi, et al.
Published: (2023)
by: Tian, Runzhi, et al.
Published: (2023)
A statistical theory of overfitting for imbalanced classification
by: Lyu, Jingyang, et al.
Published: (2025)
by: Lyu, Jingyang, et al.
Published: (2025)
SigBERT: Combining Narrative Medical Reports and Rough Path Signature Theory for Survival Risk Estimation in Oncology
by: Minchella, Paul, et al.
Published: (2025)
by: Minchella, Paul, et al.
Published: (2025)
Preventing overfitting in deep learning using differential privacy
by: Khatri, Alizishaan Anwar Hussein
Published: (2026)
by: Khatri, Alizishaan Anwar Hussein
Published: (2026)
The temporal overfitting problem with applications in wind power curve modeling
by: Prakash, Abhinav, et al.
Published: (2020)
by: Prakash, Abhinav, et al.
Published: (2020)
Benign overfitting in leaky ReLU networks with moderate input dimension
by: Karhadkar, Kedar, et al.
Published: (2024)
by: Karhadkar, Kedar, et al.
Published: (2024)
A theoretical framework for overfitting in energy-based modeling
by: Catania, Giovanni, et al.
Published: (2025)
by: Catania, Giovanni, et al.
Published: (2025)
Algorithms for ridge estimation with convergence guarantees
by: Qiao, Wanli, et al.
Published: (2021)
by: Qiao, Wanli, et al.
Published: (2021)
Efficient local linearity regularization to overcome catastrophic overfitting
by: Rocamora, Elias Abad, et al.
Published: (2024)
by: Rocamora, Elias Abad, et al.
Published: (2024)
Robustly overfitting latents for flexible neural image compression
by: Perugachi-Diaz, Yura, et al.
Published: (2024)
by: Perugachi-Diaz, Yura, et al.
Published: (2024)
Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint
by: Shi, Zhongjie, et al.
Published: (2024)
by: Shi, Zhongjie, et al.
Published: (2024)
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
by: Haas, Moritz, et al.
Published: (2023)
by: Haas, Moritz, et al.
Published: (2023)
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2023)
by: Chen, Feiyi, et al.
Published: (2023)
Generalisation and benign over-fitting for linear regression onto random functional covariates
by: Jones, Andrew, et al.
Published: (2025)
by: Jones, Andrew, et al.
Published: (2025)
Why you don't overfit, and don't need Bayes if you only train for one epoch
by: Aitchison, Laurence
Published: (2024)
by: Aitchison, Laurence
Published: (2024)
A unified construction for series representations and finite approximations of completely random measures
by: Lee, Juho, et al.
Published: (2019)
by: Lee, Juho, et al.
Published: (2019)
Open-source framework for detecting bias and overfitting for large pathology images
by: Sildnes, Anders, et al.
Published: (2025)
by: Sildnes, Anders, et al.
Published: (2025)
Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory
by: Prakash, Hari K., et al.
Published: (2026)
by: Prakash, Hari K., et al.
Published: (2026)
Optimal ridge regularization revisited
by: Timmermans, Jack, et al.
Published: (2026)
by: Timmermans, Jack, et al.
Published: (2026)
Regularization, early-stopping and dreaming: a Hopfield-like setup to address generalization and overfitting
by: Agliari, Elena, et al.
Published: (2023)
by: Agliari, Elena, et al.
Published: (2023)
Nesterov acceleration in benignly non-convex landscapes
by: Gupta, Kanan, et al.
Published: (2024)
by: Gupta, Kanan, et al.
Published: (2024)
Benign overfitting in Fixed Dimension via Physics-Informed Learning with Smooth Inductive Bias
by: Wong, Honam, et al.
Published: (2024)
by: Wong, Honam, et al.
Published: (2024)
An overview of condensation phenomenon in deep learning
by: Xu, Zhi-Qin John, et al.
Published: (2025)
by: Xu, Zhi-Qin John, et al.
Published: (2025)
Uniform convergence for Gaussian kernel ridge regression
by: Dommel, Paul, et al.
Published: (2025)
by: Dommel, Paul, et al.
Published: (2025)
Comparing regularisation paths of (conjugate) gradient estimators in ridge regression
by: Hucker, Laura, et al.
Published: (2025)
by: Hucker, Laura, et al.
Published: (2025)
Risk and cross validation in ridge regression with correlated samples
by: Atanasov, Alexander, et al.
Published: (2024)
by: Atanasov, Alexander, et al.
Published: (2024)
Analysis of Nystrom method with sequential ridge leverage scores
by: Calandriello, Daniele, et al.
Published: (2026)
by: Calandriello, Daniele, et al.
Published: (2026)
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization
by: Kobak, Dmitry, et al.
Published: (2018)
by: Kobak, Dmitry, et al.
Published: (2018)
Shapley meets Rawls: an integrated framework for measuring and explaining unfairness
by: Amri-Jouidel, Fadoua, et al.
Published: (2026)
by: Amri-Jouidel, Fadoua, et al.
Published: (2026)
Finite sample bounds for barycenter estimation in geodesic spaces
by: Brunel, Victor-Emmanuel, et al.
Published: (2025)
by: Brunel, Victor-Emmanuel, et al.
Published: (2025)
Bayesian implementation of Targeted Maximum Likelihood Estimation for uncertainty quantification in causal effect estimation
by: Nannapaneni, Saideep, et al.
Published: (2025)
by: Nannapaneni, Saideep, et al.
Published: (2025)
A transport approach to the cutoff phenomenon
by: Pedrotti, Francesco, et al.
Published: (2025)
by: Pedrotti, Francesco, et al.
Published: (2025)
Kernel ridge regression under power-law data: spectrum and generalization
by: Wortsman, Arie, et al.
Published: (2025)
by: Wortsman, Arie, et al.
Published: (2025)
Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
by: Calandriello, Daniele, et al.
Published: (2026)
by: Calandriello, Daniele, et al.
Published: (2026)
Similar Items
-
Detecting malignant dynamics on very few blood sample using signature coefficients
by: Vaucher, Rémi, et al.
Published: (2025) -
Time topological analysis of EEG using signature theory
by: Chrétien, Stéphane, et al.
Published: (2024) -
Conformal Online Learning of Deep Koopman Linear Embeddings
by: Gao, Ben, et al.
Published: (2025) -
Be aware of overfitting by hyperparameter optimization!
by: Tetko, Igor V., et al.
Published: (2024) -
Understanding overfitting in random forest for probability estimation: a visualization and simulation study
by: Barreñada, Lasai, et al.
Published: (2024)