Imagen de Portada

Meta-Learning and representation learner: A short theoretical note

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Bouchattaoui, Mouad El
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Statistics Theory
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Learning Causality for Longitudinal Data
por: Bouchattaoui, Mouad EL
Publicado: (2025)

Topological Residual Asymmetry for Bivariate Causal Direction
por: Bouchattaoui, Mouad El
Publicado: (2026)

Random Walk in Random Environment: A short introduction
por: Bouchattaoui, Mouad El
Publicado: (2024)

Information-theoretic Limits of Learning and Estimation
por: Gamal, Abbas El, et al.
Publicado: (2026)

Causal Contrastive Learning for Counterfactual Regression Over Time
por: Bouchattaoui, Mouad El, et al.
Publicado: (2024)

A Unified Information-Theoretic Framework for Meta-Learning Generalization
por: Wen, Wen, et al.
Publicado: (2025)

A theoretical framework for M-posteriors: frequentist guarantees and robustness properties
por: Marusic, Juraj, et al.
Publicado: (2025)

Information-theoretic Generalization Analysis for Expected Calibration Error
por: Futami, Futoshi, et al.
Publicado: (2024)

Nonlinear Meta-Learning Can Guarantee Faster Rates
por: Meunier, Dimitri, et al.
Publicado: (2023)

Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data
por: Bouchattaoui, Mouad El, et al.
Publicado: (2023)

On the Efficiency of ERM in Feature Learning
por: Hanchi, Ayoub El, et al.
Publicado: (2024)

A unified construction for series representations and finite approximations of completely random measures
por: Lee, Juho, et al.
Publicado: (2019)

Smoothed SGD for quantiles: Bahadur representation and Gaussian approximation
por: Chen, Likai, et al.
Publicado: (2025)

Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
por: Jin, Yanhao, et al.
Publicado: (2024)

The Strong, Weak and Benign Goodhart's law. An independence-free and paradigm-agnostic formalisation
por: Majka, Adrien, et al.
Publicado: (2025)

MetaCURL: Non-stationary Concave Utility Reinforcement Learning
por: Moreno, Bianca Marin, et al.
Publicado: (2024)

Consistent estimation of generative model representations in the data kernel perspective space
por: Acharyya, Aranyak, et al.
Publicado: (2024)

A theoretical perspective on mode collapse in variational inference
por: Soletskyi, Roman, et al.
Publicado: (2024)

A Geometric Analysis of PCA
por: Hanchi, Ayoub El, et al.
Publicado: (2025)

Beyond identifiability: Learning causal representations with few environments and finite samples
por: Lee, Inbeom, et al.
Publicado: (2026)

Convergence of Statistical Estimators via Mutual Information Bounds
por: Khribch, El Mahdi, et al.
Publicado: (2024)

Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis
por: Khellaf, Rémi, et al.
Publicado: (2024)

Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$-Norm Linear Regression
por: Hanchi, Ayoub El, et al.
Publicado: (2023)

The loss landscape of deep linear neural networks: a second-order analysis
por: Achour, El Mehdi, et al.
Publicado: (2021)

On Monotonicity in AI Alignment
por: Bareilles, Gilles, et al.
Publicado: (2025)

A note on the impossibility of conditional PAC-efficient reasoning in large language models
por: Zeng, Hao
Publicado: (2025)

General reproducing properties in RKHS with application to derivative and integral operators
por: El-Boukkouri, Fatima-Zahrae, et al.
Publicado: (2025)

A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces
por: Wynne, George, et al.
Publicado: (2022)

Minimax Linear Regression under the Quantile Risk
por: Hanchi, Ayoub El, et al.
Publicado: (2024)

A note on the unique properties of the Kullback--Leibler divergence for sampling via gradient flows
por: Crucinio, Francesca Romana
Publicado: (2025)

What is causal about causal models and representations?
por: Jørgensen, Frederik Hytting, et al.
Publicado: (2025)

PLS-based approach for fair representation learning
por: De-Diego, Elena M., et al.
Publicado: (2025)

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
por: Elliott, Chris, et al.
Publicado: (2026)

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

Optimal rates for density and mode estimation with expand-and-sparsify representations
por: Sinha, Kaushik, et al.
Publicado: (2026)

Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemia
por: Gachon, Erell, et al.
Publicado: (2024)

On Goodhart's law, with an application to value alignment
por: El-Mhamdi, El-Mahdi, et al.
Publicado: (2024)

Transformers Meet In-Context Learning: A Universal Approximation Theory
por: Li, Gen, et al.
Publicado: (2025)

Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
por: Kim, Gilhan
Publicado: (2026)

A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
por: Lin, Licong, et al.
Publicado: (2025)