Cover Image

Local versions of sum-of-norms clustering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dunlap, Alexander, Mourrat, Jean-Christophe
Format:	Preprint
Published:	2021
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sum-of-norms clustering does not separate nearby balls
by: Dunlap, Alexander, et al.
Published: (2021)

Mixture of multilayer stochastic block models for multiview clustering
by: De Santiago, Kylliann, et al.
Published: (2024)

Scalable and adaptive prediction bands with kernel sum-of-squares
by: Allain, Louis, et al.
Published: (2025)

A path-norm toolkit for modern networks: consequences, promises and challenges
by: Gonon, Antoine, et al.
Published: (2023)

Generalization error of min-norm interpolators in transfer learning
by: Song, Yanke, et al.
Published: (2024)

Semidefinite programming relaxations and debiasing for MAXCUT-based clustering
by: Zhou, Shuheng
Published: (2024)

Computational lower bounds in latent models: clustering, sparse-clustering, biclustering
by: Even, Bertrand, et al.
Published: (2025)

Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias
by: Zhang, Shuofeng, et al.
Published: (2025)

The generalized underlap coefficient with an application in clustering
by: Zhang, Zhaoxi, et al.
Published: (2026)

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities
by: Carpentier, Alexandra, et al.
Published: (2025)

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities (II)
by: Carpentier, Alexandra, et al.
Published: (2025)

Low-degree Lower bounds for clustering in moderate dimension
by: Carpentier, Alexandra, et al.
Published: (2026)

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

Local Minima Structures in Gaussian Mixture Models
by: Chen, Yudong, et al.
Published: (2020)

Local Polynomial Lp-norm Regression
by: Tazik, Ladan, et al.
Published: (2025)

Minimax-optimal and Locally-adaptive Online Nonparametric Regression
by: Liautaud, Paul, et al.
Published: (2024)

Scalable multitask Gaussian processes for complex mechanical systems with functional covariates
by: Gninkou, Razak Christophe Sabi, et al.
Published: (2026)

Bounds in Wasserstein Distance for Locally Stationary Functional Time Series
by: Tinio, Jan Nino G., et al.
Published: (2025)

Triple Component Matrix Factorization: Untangling Global, Local, and Noisy Components
by: Shi, Naichen, et al.
Published: (2024)

Upper Bounds for Local Learning Coefficients of Three-Layer Neural Networks
by: Kurumadani, Yuki
Published: (2026)

Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
by: Li, Zheng, et al.
Published: (2024)

Local minima of the empirical risk in high dimension: General theorems and convex examples
by: Asgari, Kiana, et al.
Published: (2025)

Further Understanding of a Local Gaussian Process Approximation: Characterising Convergence in the Finite Regime
by: Stephenson, Anthony, et al.
Published: (2024)

Precise Error Rates for Computationally Efficient Testing
by: Moitra, Ankur, et al.
Published: (2023)

Locally Near Optimal Piecewise Linear Regression in High Dimensions via Difference of Max-Affine Functions
by: Kanj, Haitham, et al.
Published: (2026)

Sparsified-Learning for High-Dimensional Heavy-Tailed Locally Stationary Time Series, Concentration and Oracle Inequalities
by: Wang, Yingjie, et al.
Published: (2025)

Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula
by: Chatterjee, Sabyasachi
Published: (2024)

Random Matrix Theory of Early-Stopped Gradient Flow: A Transient BBP Scenario
by: Coeurdoux, Florentin, et al.
Published: (2026)

Testing for correlation between network structure and high-dimensional node covariates
by: Fuchs-Kreiss, Alexander, et al.
Published: (2025)

Local Poisson Deconvolution for Discrete Signals
by: Hundrieser, Shayan, et al.
Published: (2025)

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

Uniform Laws of Large Numbers in Product Spaces
by: Holzman, Ron, et al.
Published: (2026)

Refined Risk Bounds for Unbounded Losses via Transductive Priors
by: Qian, Jian, et al.
Published: (2024)

A Gapped Scale-Sensitive Dimension and Lower Bounds for Offset Rademacher Complexity
by: Jia, Zeyu, et al.
Published: (2025)

Tessellation Localized Transfer learning for nonparametric regression
by: Halconruy, Hélène, et al.
Published: (2026)

Locally minimax optimal confidence sets for the best model
by: Kim, Ilmun, et al.
Published: (2025)

The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
by: Cohen, Doron, et al.
Published: (2024)

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

Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression
by: Chen, Fan, et al.
Published: (2026)

High-accuracy sampling for diffusion models and log-concave distributions
by: Chen, Fan, et al.
Published: (2026)