:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Averyanov, Yaroslav, Celisse, Alain
Formato:	Preprint
Publicado:	2020
Materias:	Machine Learning Statistics Theory
Acceso en línea:	https://arxiv.org/abs/2008.08718
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Early stopping and polynomial smoothing in regression with reproducing kernels
por: Averyanov, Yaroslav, et al.
Publicado: (2020)

Approximate full conformal prediction in an RKHS
por: Razafindrakoto, Davidson Lova, et al.
Publicado: (2026)

Representation learning with a transformer by contrastive learning for money laundering detection
por: Guéneau, Harold, et al.
Publicado: (2025)

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
por: Lugosi, Gábor, et al.
Publicado: (2025)

Improved convergence rate of kNN graph Laplacians: differentiable self-tuned affinity
por: Cheng, Xiuyuan, et al.
Publicado: (2024)

Deep regression learning from dependent observations with minimum error entropy principle
por: Kengne, William, et al.
Publicado: (2026)

Bagged Regularized $k$-Distances for Anomaly Detection
por: Cai, Yuchao, et al.
Publicado: (2023)

Maximum mean discrepancies of Farey sequences
por: Karvonen, Toni, et al.
Publicado: (2024)

Asymptotic Theory of Geometric and Adaptive $k$-Means Clustering
por: Jaffe, Adam Quinn
Publicado: (2022)

Minimax Limits of k-Fold Cross-Validation via Majority
por: Nachum, Ido, et al.
Publicado: (2026)

Foundations of Top-$k$ Decoding For Language Models
por: Noarov, Georgy, et al.
Publicado: (2025)

kNNSampler: Stochastic Imputations for Recovering Missing Value Distributions
por: Pashmchi, Parastoo, et al.
Publicado: (2025)

The Catastrophic Failure of The k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It
por: Lederman, Roy R., et al.
Publicado: (2026)

One-Shot Learning for k-SAT
por: Galanis, Andreas, et al.
Publicado: (2025)

An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
por: Düngler, Johanna, et al.
Publicado: (2025)

A Note on k-NN Gating in RAG
por: Biau, Gérard, et al.
Publicado: (2026)

Nonparametric logistic regression with deep learning
por: Yara, Atsutomo, et al.
Publicado: (2024)

Metric space valued Fréchet regression
por: Györfi, László, et al.
Publicado: (2026)

On damage of interpolation to adversarial robustness in regression
por: Peng, Jingfu, et al.
Publicado: (2026)

Minimax Optimal Algorithms with Fixed-$k$-Nearest Neighbors
por: Ryu, J. Jon, et al.
Publicado: (2022)

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients
por: Lytras, Iosif, et al.
Publicado: (2025)

Dynamical local Fréchet curve regression in manifolds
por: Ruiz-Medina, M. D., et al.
Publicado: (2025)

Covariate shift in nonparametric regression with Markovian design
por: Trottner, Lukas
Publicado: (2023)

Exploring the Limitations of kNN Noisy Feature Detection and Recovery for Self-Driving Labs
por: Shi, Qiuyu, et al.
Publicado: (2025)

Outrigger local polynomial regression
por: Young, Elliot H., et al.
Publicado: (2026)

Support estimation in high-dimensional heteroscedastic mean regression
por: Hermann, Philipp, et al.
Publicado: (2020)

Infinitely divisible privacy and beyond I: resolution of the $s^2=2k$ conjecture
por: Pandey, Aaradhya, et al.
Publicado: (2025)

Adaptive sparse variational approximations for Gaussian process regression
por: Nieman, Dennis, et al.
Publicado: (2025)

Strong identifiability and parameter learning in regression with heterogeneous response
por: Do, Dat, et al.
Publicado: (2022)

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)

Finite-sample performance of the maximum likelihood estimator in logistic regression
por: Chardon, Hugo, et al.
Publicado: (2024)

Minimax rates of convergence for nonparametric regression under adversarial attacks
por: Peng, Jingfu, et al.
Publicado: (2024)

Minimax optimal transfer learning for high-dimensional additive regression
por: Moon, Seung Hyun
Publicado: (2025)

Canonical correlation regression with noisy data
por: Meza, Isaac, et al.
Publicado: (2025)

Batches Stabilize the Minimum Norm Risk in High Dimensional Overparameterized Linear Regression
por: Ioushua, Shahar Stein, et al.
Publicado: (2023)

On the sample complexity of parameter estimation in logistic regression with normal design
por: Hsu, Daniel, et al.
Publicado: (2023)

Parametric Mean-Field empirical Bayes in high-dimensional linear regression
por: Lee, Seunghyun, et al.
Publicado: (2026)

High-dimensional logistic regression with missing data: Imputation, regularization, and universality
por: Verchand, Kabir Aladin, et al.
Publicado: (2024)

Improved learning theory for kernel distribution regression with two-stage sampling
por: Bachoc, François, et al.
Publicado: (2023)

Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
por: You, Kisung
Publicado: (2026)