Improved convergence rate of kNN graph Laplacians: differentiable self-tuned affinity
Fuente:
arXiv
Saved in:
| Main Authors: | Cheng, Xiuyuan, Tan, Yixuan, Wu, Nan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
by: Cheng, Xiuyuan, et al.
Published: (2021)
by: Cheng, Xiuyuan, et al.
Published: (2021)
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise
by: Cheng, Xiuyuan, et al.
Published: (2022)
by: Cheng, Xiuyuan, et al.
Published: (2022)
Learning manifold diffusion semigroups from graph transition matrices
by: Cheng, Xiuyuan, et al.
Published: (2026)
by: Cheng, Xiuyuan, et al.
Published: (2026)
Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
by: Lugosi, Gábor, et al.
Published: (2025)
by: Lugosi, Gábor, et al.
Published: (2025)
Flow-based generative models as iterative algorithms in probability space
by: Xie, Yao, et al.
Published: (2025)
by: Xie, Yao, et al.
Published: (2025)
Kernel Two-Sample Tests for Manifold Data
by: Cheng, Xiuyuan, et al.
Published: (2021)
by: Cheng, Xiuyuan, et al.
Published: (2021)
Minimum discrepancy principle strategy for choosing $k$ in $k$-NN regression
by: Averyanov, Yaroslav, et al.
Published: (2020)
by: Averyanov, Yaroslav, et al.
Published: (2020)
Exploring the Limitations of kNN Noisy Feature Detection and Recovery for Self-Driving Labs
by: Shi, Qiuyu, et al.
Published: (2025)
by: Shi, Qiuyu, et al.
Published: (2025)
Point processes with event time uncertainty
by: Cheng, Xiuyuan, et al.
Published: (2024)
by: Cheng, Xiuyuan, et al.
Published: (2024)
Deep spatio-temporal point processes: Advances and new directions
by: Cheng, Xiuyuan, et al.
Published: (2025)
by: Cheng, Xiuyuan, et al.
Published: (2025)
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
by: Cheng, Xiuyuan, et al.
Published: (2023)
by: Cheng, Xiuyuan, et al.
Published: (2023)
On the rates of convergence for learning with convolutional neural networks
by: Yang, Yunfei, et al.
Published: (2024)
by: Yang, Yunfei, et al.
Published: (2024)
kNN-Graph: An adaptive graph model for $k$-nearest neighbors
by: Li, Jiaye, et al.
Published: (2026)
by: Li, Jiaye, et al.
Published: (2026)
Minimax rates of convergence for nonparametric regression under adversarial attacks
by: Peng, Jingfu, et al.
Published: (2024)
by: Peng, Jingfu, et al.
Published: (2024)
On the rate of convergence of an over-parametrized Transformer classifier learned by gradient descent
by: Kohler, Michael, et al.
Published: (2023)
by: Kohler, Michael, et al.
Published: (2023)
Online selective conformal inference: adaptive scores, convergence rate and optimality
by: Humbert, Pierre, et al.
Published: (2025)
by: Humbert, Pierre, et al.
Published: (2025)
GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
by: Bou-Rabee, Nawaf, et al.
Published: (2024)
by: Bou-Rabee, Nawaf, et al.
Published: (2024)
Implicit score matching meets denoising score matching: improved rates of convergence and log-density Hessian estimation
by: Yakovlev, Konstantin, et al.
Published: (2025)
by: Yakovlev, Konstantin, et al.
Published: (2025)
Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Rates of convergence for density estimation with generative adversarial networks
by: Puchkin, Nikita, et al.
Published: (2021)
by: Puchkin, Nikita, et al.
Published: (2021)
Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
by: Fan, Jianqing, et al.
Published: (2025)
by: Fan, Jianqing, et al.
Published: (2025)
Gradient dynamics for low-rank fine-tuning beyond kernels
by: Dayi, Arif Kerem, et al.
Published: (2024)
by: Dayi, Arif Kerem, et al.
Published: (2024)
Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuning
by: Patil, Pratik, et al.
Published: (2023)
by: Patil, Pratik, et al.
Published: (2023)
Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning
by: Bellec, Pierre C, et al.
Published: (2021)
by: Bellec, Pierre C, et al.
Published: (2021)
New affine invariant ensemble samplers and their dimensional scaling
by: Chen, Yifan
Published: (2025)
by: Chen, Yifan
Published: (2025)
Bagged Regularized $k$-Distances for Anomaly Detection
by: Cai, Yuchao, et al.
Published: (2023)
by: Cai, Yuchao, et al.
Published: (2023)
Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
by: Bonnerjee, Soham, et al.
Published: (2026)
by: Bonnerjee, Soham, et al.
Published: (2026)
Asymptotic Theory of Geometric and Adaptive $k$-Means Clustering
by: Jaffe, Adam Quinn
Published: (2022)
by: Jaffe, Adam Quinn
Published: (2022)
Adaptive Bayesian Regression on Data with Low Intrinsic Dimensionality
by: Tang, Tao, et al.
Published: (2024)
by: Tang, Tao, et al.
Published: (2024)
Improved Scaling Laws in Linear Regression via Data Reuse
by: Lin, Licong, et al.
Published: (2025)
by: Lin, Licong, et al.
Published: (2025)
Minimax Limits of k-Fold Cross-Validation via Majority
by: Nachum, Ido, et al.
Published: (2026)
by: Nachum, Ido, et al.
Published: (2026)
Distributed quasi-Newton robust estimation under differential privacy
by: Wang, Chuhan, et al.
Published: (2024)
by: Wang, Chuhan, et al.
Published: (2024)
Variance estimation in graphs with the fused lasso
by: Padilla, Oscar Hernan Madrid
Published: (2022)
by: Padilla, Oscar Hernan Madrid
Published: (2022)
Optimal community detection in dense bipartite graphs
by: Chhor, Julien, et al.
Published: (2025)
by: Chhor, Julien, et al.
Published: (2025)
Asymptotic spectrum of weighted sample covariance: another proof of spectrum convergence
by: Oriol, Benoit
Published: (2024)
by: Oriol, Benoit
Published: (2024)
kNN Classification of Malware Data Dependency Graph Features
by: Musgrave, John, et al.
Published: (2024)
by: Musgrave, John, et al.
Published: (2024)
The Catastrophic Failure of The k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It
by: Lederman, Roy R., et al.
Published: (2026)
by: Lederman, Roy R., et al.
Published: (2026)
Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity
by: Martinez-Taboada, Diego, et al.
Published: (2025)
by: Martinez-Taboada, Diego, et al.
Published: (2025)
Statistical-computational gap in multiple Gaussian graph alignment
by: Even, Bertrand, et al.
Published: (2025)
by: Even, Bertrand, et al.
Published: (2025)
Nonparametric spectral density estimation using interactive mechanisms under local differential privacy
by: Butucea, Cristina, et al.
Published: (2025)
by: Butucea, Cristina, et al.
Published: (2025)
Similar Items
-
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
by: Cheng, Xiuyuan, et al.
Published: (2021) -
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise
by: Cheng, Xiuyuan, et al.
Published: (2022) -
Learning manifold diffusion semigroups from graph transition matrices
by: Cheng, Xiuyuan, et al.
Published: (2026) -
Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
by: Lugosi, Gábor, et al.
Published: (2025) -
Flow-based generative models as iterative algorithms in probability space
by: Xie, Yao, et al.
Published: (2025)