A Margin-based Multiclass Generalization Bound via Geometric Complexity
Fuente:
arXiv
Saved in:
| Main Authors: | Munn, Michael, Dherin, Benoit, Gonzalvo, Javier |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
by: Munn, Michael, et al.
Published: (2024)
by: Munn, Michael, et al.
Published: (2024)
Equivalence of Context and Parameter Updates in Modern Transformer Blocks
by: Goldwaser, Adrian, et al.
Published: (2025)
by: Goldwaser, Adrian, et al.
Published: (2025)
Transmuting prompts into weights
by: Mazzawi, Hanna, et al.
Published: (2025)
by: Mazzawi, Hanna, et al.
Published: (2025)
On residual network depth
by: Dherin, Benoit, et al.
Published: (2025)
by: Dherin, Benoit, et al.
Published: (2025)
Learning without training: The implicit dynamics of in-context learning
by: Dherin, Benoit, et al.
Published: (2025)
by: Dherin, Benoit, et al.
Published: (2025)
Learning by solving differential equations
by: Dherin, Benoit, et al.
Published: (2025)
by: Dherin, Benoit, et al.
Published: (2025)
How iteration order influences convergence and stability in deep learning
by: Dherin, Benoit, et al.
Published: (2025)
by: Dherin, Benoit, et al.
Published: (2025)
Deep Fusion: Efficient Network Training via Pre-trained Initializations
by: Mazzawi, Hanna, et al.
Published: (2023)
by: Mazzawi, Hanna, et al.
Published: (2023)
Grow, Don't Overwrite: Fine-tuning Without Forgetting
by: Adila, Dyah, et al.
Published: (2026)
by: Adila, Dyah, et al.
Published: (2026)
Corridor Geometry in Gradient-Based Optimization
by: Dherin, Benoit, et al.
Published: (2024)
by: Dherin, Benoit, et al.
Published: (2024)
Unified Binary and Multiclass Margin-Based Classification
by: Wang, Yutong, et al.
Published: (2023)
by: Wang, Yutong, et al.
Published: (2023)
A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
by: Munn, Michael, et al.
Published: (2024)
by: Munn, Michael, et al.
Published: (2024)
Lower Bounds on Adversarial Robustness for Multiclass Classification with General Loss Functions
by: Trillos, Camilo Andrés García, et al.
Published: (2025)
by: Trillos, Camilo Andrés García, et al.
Published: (2025)
The Optimal Sample Complexity of Multiclass and List Learning
by: Pabbaraju, Chirag
Published: (2026)
by: Pabbaraju, Chirag
Published: (2026)
Geometric States
by: Dherin, Benoit, et al.
Published: (2024)
by: Dherin, Benoit, et al.
Published: (2024)
A Robust Twin Parametric Margin Support Vector Machine for Multiclass Classification
by: De Leone, Renato, et al.
Published: (2023)
by: De Leone, Renato, et al.
Published: (2023)
Multiclass threshold-based classification
by: Marchetti, Francesco, et al.
Published: (2025)
by: Marchetti, Francesco, et al.
Published: (2025)
Multiclass Graph-Based Large Margin Classifiers: Unified Approach for Support Vectors and Neural Networks
by: Hanriot, Vítor M., et al.
Published: (2025)
by: Hanriot, Vítor M., et al.
Published: (2025)
The Sample Complexity of Multiclass and Sparse Contextual Bandits
by: Erez, Liad, et al.
Published: (2026)
by: Erez, Liad, et al.
Published: (2026)
Multiclass threshold-based classification and model evaluation
by: Legnaro, Edoardo, et al.
Published: (2025)
by: Legnaro, Edoardo, et al.
Published: (2025)
Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back
by: Cohen, Alon, et al.
Published: (2025)
by: Cohen, Alon, et al.
Published: (2025)
Tight Generalization Bounds for Large-Margin Halfspaces
by: Larsen, Kasper Green, et al.
Published: (2025)
by: Larsen, Kasper Green, et al.
Published: (2025)
Multiclass ROC
by: Wang, Liang, et al.
Published: (2024)
by: Wang, Liang, et al.
Published: (2024)
On Rademacher Complexity-based Generalization Bounds for Deep Learning
by: Truong, Lan V.
Published: (2022)
by: Truong, Lan V.
Published: (2022)
A Bound on the Maximal Marginal Degrees of Freedom
by: Dommel, Paul
Published: (2024)
by: Dommel, Paul
Published: (2024)
An Optimal Transport Approach for Computing Adversarial Training Lower Bounds in Multiclass Classification
by: Trillos, Nicolas Garcia, et al.
Published: (2024)
by: Trillos, Nicolas Garcia, et al.
Published: (2024)
A Multiclass ROC Curve
by: Giudici, Paolo, et al.
Published: (2025)
by: Giudici, Paolo, et al.
Published: (2025)
Wasserstein Distributionally Robust Multiclass Support Vector Machine
by: Ibrahim, Michael, et al.
Published: (2024)
by: Ibrahim, Michael, et al.
Published: (2024)
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models
by: Wu, David X., et al.
Published: (2023)
by: Wu, David X., et al.
Published: (2023)
Scalable Utility-Aware Multiclass Calibration
by: Hegazy, Mahmoud, et al.
Published: (2025)
by: Hegazy, Mahmoud, et al.
Published: (2025)
Multiclass Transductive Online Learning
by: Hanneke, Steve, et al.
Published: (2024)
by: Hanneke, Steve, et al.
Published: (2024)
On the Computability of Multiclass PAC Learning
by: Gourdeau, Pascale, et al.
Published: (2025)
by: Gourdeau, Pascale, et al.
Published: (2025)
Regularization and Optimal Multiclass Learning
by: Asilis, Julian, et al.
Published: (2023)
by: Asilis, Julian, et al.
Published: (2023)
Improved Margin Generalization Bounds for Voting Classifiers
by: Høgsgaard, Mikael Møller, et al.
Published: (2025)
by: Høgsgaard, Mikael Møller, et al.
Published: (2025)
Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification
by: Schliserman, Matan, et al.
Published: (2025)
by: Schliserman, Matan, et al.
Published: (2025)
MISS: Multiclass Interpretable Scoring Systems
by: Grzeszczyk, Michal K., et al.
Published: (2024)
by: Grzeszczyk, Michal K., et al.
Published: (2024)
Universal Multiclass Transductive Online Learning
by: Hanneke, Steve, et al.
Published: (2026)
by: Hanneke, Steve, et al.
Published: (2026)
Kernel Density Estimation for Multiclass Quantification
by: Moreo, Alejandro, et al.
Published: (2023)
by: Moreo, Alejandro, et al.
Published: (2023)
The Geometric Cost of Normalization: Affine Bounds on the Bayesian Complexity of Neural Networks
by: Chun, Sungbae
Published: (2026)
by: Chun, Sungbae
Published: (2026)
A Unified Geometric Framework for Weighted Contrastive Learning
by: Vock, Raphael, et al.
Published: (2026)
by: Vock, Raphael, et al.
Published: (2026)
Similar Items
-
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
by: Munn, Michael, et al.
Published: (2024) -
Equivalence of Context and Parameter Updates in Modern Transformer Blocks
by: Goldwaser, Adrian, et al.
Published: (2025) -
Transmuting prompts into weights
by: Mazzawi, Hanna, et al.
Published: (2025) -
On residual network depth
by: Dherin, Benoit, et al.
Published: (2025) -
Learning without training: The implicit dynamics of in-context learning
by: Dherin, Benoit, et al.
Published: (2025)