Imagen de Portada

Universal Rates of Empirical Risk Minimization

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Hanneke, Steve, Xu, Mingyue
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Universal rates of ERM for agnostic learning
por: Hanneke, Steve, et al.
Publicado: (2025)

When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
por: Hanneke, Steve, et al.
Publicado: (2026)

Universal Multiclass Transductive Online Learning
por: Hanneke, Steve, et al.
Publicado: (2026)

A Theory of Optimistically Universal Online Learnability for General Concept Classes
por: Hanneke, Steve, et al.
Publicado: (2025)

A Theory of Universal Agnostic Learning
por: Hanneke, Steve, et al.
Publicado: (2026)

The Dimension of Self-Directed Learning
por: Devulapalli, Pramith, et al.
Publicado: (2024)

Learning from Snapshots of Discrete and Continuous Data Streams
por: Devulapalli, Pramith, et al.
Publicado: (2024)

On Characterizing Learnability for Adversarial Noisy Bandits
por: Hanneke, Steve, et al.
Publicado: (2026)

Adversarially Robust PAC Learnability of Real-Valued Functions
por: Attias, Idan, et al.
Publicado: (2022)

A Complete Characterization of Learnability for Stochastic Noisy Bandits
por: Hanneke, Steve, et al.
Publicado: (2024)

Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
por: Yaakoubi, Chiheb, et al.
Publicado: (2026)

Adaptive Sample Aggregation In Transfer Learning
por: Hanneke, Steve, et al.
Publicado: (2024)

Sample Compression Scheme Reductions
por: Attias, Idan, et al.
Publicado: (2024)

List Sample Compression and Uniform Convergence
por: Hanneke, Steve, et al.
Publicado: (2024)

Regret-Oracle Complexity Tradeoffs in Agnostic Online Learning
por: Attias, Idan, et al.
Publicado: (2026)

Sample Complexity of Autoregressive Reasoning: Chain-of-Thought vs. End-to-End
por: Hanneke, Steve, et al.
Publicado: (2026)

Uniform Convergence Beyond Glivenko-Cantelli
por: Devale, Tanmay, et al.
Publicado: (2025)

A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability
por: Attias, Idan, et al.
Publicado: (2022)

On the Performance of Empirical Risk Minimization with Smoothed Data
por: Block, Adam, et al.
Publicado: (2024)

Empirical Risk Minimization with $f$-Divergence Regularization
por: Daunas, Francisco, et al.
Publicado: (2026)

Efficient Agnostic Learning with Average Smoothness
por: Hanneke, Steve, et al.
Publicado: (2023)

Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
por: Attias, Idan, et al.
Publicado: (2025)

On the Variance, Admissibility, and Stability of Empirical Risk Minimization
por: Kur, Gil, et al.
Publicado: (2023)

A Researcher's Guide to Empirical Risk Minimization
por: van der Laan, Lars
Publicado: (2026)

On the ERM Principle in Meta-Learning
por: Alon, Yannay, et al.
Publicado: (2024)

Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs
por: Filmus, Yuval, et al.
Publicado: (2024)

Multiclass Transductive Online Learning
por: Hanneke, Steve, et al.
Publicado: (2024)

Data Selection for ERMs
por: Hanneke, Steve, et al.
Publicado: (2025)

Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension
por: Filmus, Yuval, et al.
Publicado: (2023)

On Union-Closedness of Language Generation
por: Hanneke, Steve, et al.
Publicado: (2025)

Proofs as Explanations: Short Certificates for Reliable Predictions
por: Blum, Avrim, et al.
Publicado: (2025)

An Optimal Sauer Lemma Over $k$-ary Alphabets
por: Hanneke, Steve, et al.
Publicado: (2026)

Optimal Mistake Bounds for Transductive Online Learning
por: Chase, Zachary, et al.
Publicado: (2025)

Asymmetry of the Relative Entropy in the Regularization of Empirical Risk Minimization
por: Daunas, Francisco, et al.
Publicado: (2024)

Fast Rates for Nonstationary Weighted Risk Minimization
por: Brock, Tobias, et al.
Publicado: (2026)

Optimal Empirical Risk Minimization under Temporal Distribution Shifts
por: Jeong, Yujin, et al.
Publicado: (2025)

Asymptotic Theory of Iterated Empirical Risk Minimization, with Applications to Active Learning
por: Cui, Hugo, et al.
Publicado: (2026)

Empirical Risk Minimization with Relative Entropy Regularization
por: Perlaza, Samir M., et al.
Publicado: (2022)

Equivalence of the Empirical Risk Minimization to Regularization on the Family of f-Divergences
por: Daunas, Francisco, et al.
Publicado: (2024)

f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
por: Baharlouei, Sina, et al.
Publicado: (2023)