Cover Image

Sharp Bounds for Poly-GNNs and the Effect of Graph Noise

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vinas, Luciano, Amini, Arash A.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Simple GNNs with Low Rank Non-parametric Aggregators
by: Vinas, Luciano, et al.
Published: (2023)

Wasserstein Concentration of Empirical Measures for Dependent Data via the Method of Moments
by: Amini, Arash A., et al.
Published: (2026)

Learning general conditional independence structures via the neighbourhood lattice
by: Amini, Arash A., et al.
Published: (2022)

Sharp Risk Bounds for Early-Stopping in Gaussian Linear Regression
by: Wegel, Tobias, et al.
Published: (2025)

Towards Sharp Minimax Risk Bounds for Operator Learning
by: Adcock, Ben, et al.
Published: (2025)

Sharp Structure-Agnostic Lower Bounds for General Linear Functional Estimation
by: Jin, Jikai, et al.
Published: (2025)

Network two-sample test for block models
by: Nguen, Chung Kyong, et al.
Published: (2024)

Sharp Gaussian approximations for Decentralized Federated Learning
by: Bonnerjee, Soham, et al.
Published: (2025)

Simplicity Bias via Global Convergence of Sharpness Minimization
by: Gatmiry, Khashayar, et al.
Published: (2024)

Sharp concentration of uniform generalization errors in binary linear classification
by: Nakakita, Shogo
Published: (2025)

Training Diagonal Linear Networks with Stochastic Sharpness-Aware Minimization
by: Clara, Gabriel, et al.
Published: (2025)

Sharp bounds on aggregate expert error
by: Kontorovich, Aryeh, et al.
Published: (2024)

Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
by: Jung, Joonhyuk, et al.
Published: (2026)

Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
by: Bonnerjee, Soham, et al.
Published: (2026)

The Adaptivity Barrier in Batched Nonparametric Bandits: Sharp Characterization of the Price of Unknown Margin
by: Jiang, Rong, et al.
Published: (2025)

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees
by: Dmitriev, Daniil, et al.
Published: (2026)

Minimax optimal submatrix detection: Sharp non-asymptotic rates
by: Knight, Parker, et al.
Published: (2026)

Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory
by: Fu, Hengyu, et al.
Published: (2024)

High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise
by: Armacki, Aleksandar, et al.
Published: (2023)

PAC-Chernoff Bounds: Understanding Generalization in the Interpolation Regime
by: Masegosa, Andrés R., et al.
Published: (2023)

Sharp Concentration Inequalities: Phase Transition and Mixing of Orlicz Tails with Variance
by: Shen, Yinan, et al.
Published: (2026)

Generator Identification for Linear SDEs with Additive and Multiplicative Noise
by: Wang, Yuanyuan, et al.
Published: (2023)

Improved Algorithm and Bounds for Successive Projection
by: Jin, Jiashun, et al.
Published: (2024)

On the Natural Gradient of the Evidence Lower Bound
by: Ay, Nihat, et al.
Published: (2023)

Optimal Lower Bounds for Online Multicalibration
by: Collina, Natalie, et al.
Published: (2026)

Feature Incremental Clustering with Generalization Bounds
by: Zhang, Jing, et al.
Published: (2026)

Sharp One-Dimensional Sub-Gaussian Comparison in Convex Order
by: Zhang, Yihan
Published: (2026)

Sharp Generalization Bounds for Foundation Models with Asymmetric Randomized Low-Rank Adapters
by: Kratsios, Anastasis, et al.
Published: (2025)

Sharp Generalization for Nonparametric Regression in Interpolation Space by Over-Parameterized Neural Networks Trained with Preconditioned Gradient Descent and Early Stopping
by: Yang, Yingzhen, et al.
Published: (2024)

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

Bounds in Wasserstein Distance for Locally Stationary Processes
by: Tinio, Jan Nino G., et al.
Published: (2024)

Adversarial Surrogate Risk Bounds for Binary Classification
by: Frank, Natalie S.
Published: (2025)

Lower Bounds on the Size of Markov Equivalence Classes
by: Jahn, Erik, et al.
Published: (2025)

Bounding Neyman-Pearson Region with $f$-Divergences
by: Mullhaupt, Andrew, et al.
Published: (2025)

Tight Generalization Bounds for Large-Margin Halfspaces
by: Larsen, Kasper Green, et al.
Published: (2025)

Comparing Comparators in Generalization Bounds
by: Hellström, Fredrik, et al.
Published: (2023)

An Upper Confidence Bound Approach to Estimating the Maximum Mean
by: Kun, Zhang, et al.
Published: (2024)

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

Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms
by: Réveillard, William, et al.
Published: (2025)

Optimal Bounds for Tyler's M-Estimator for Elliptical Distributions
by: Lau, Lap Chi, et al.
Published: (2025)