Cover Image

Divergence of Empirical Neural Tangent Kernel in Classification Problems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Zixiong, Tian, Songtao, Chen, Guhan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
by: Chen, Guhan, et al.
Published: (2024)

On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains
by: Li, Yicheng, et al.
Published: (2023)

Fast Graph Condensation with Structure-based Neural Tangent Kernel
by: Wang, Lin, et al.
Published: (2023)

Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
by: Liu, Jingren, et al.
Published: (2024)

Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets
by: Yu, Zixiong, et al.
Published: (2024)

Differential Privacy Mechanisms in Neural Tangent Kernel Regression
by: Gu, Jiuxiang, et al.
Published: (2024)

When and Why Adversarial Training Improves PINNs: A Neural Tangent Kernel Perspective
by: Cao, Yuan-dong, et al.
Published: (2026)

The Positivity of the Neural Tangent Kernel
by: Carvalho, Luís, et al.
Published: (2024)

NTKMTL: Mitigating Task Imbalance in Multi-Task Learning from Neural Tangent Kernel Perspective
by: Qin, Xiaohan, et al.
Published: (2025)

Unveiling the Mechanism of Continuous Representation Full-Waveform Inversion: A Wave Based Neural Tangent Kernel Framework
by: Chen, Ruihua, et al.
Published: (2026)

Multi-scale Wasserstein Shortest-path Graph Kernels for Graph Classification
by: Ye, Wei, et al.
Published: (2022)

The Neural Tangent Kernel for Classification
by: Plenk, Jonathan, et al.
Published: (2026)

Path-Coordinated Continual Learning with Neural Tangent Kernel-Justified Plasticity: A Theoretical Framework with Near State-of-the-Art Performance
by: Shit, Rathin Chandra
Published: (2025)

A Unified Kernel for Neural Network Learning
by: Zhang, Shao-Qun, et al.
Published: (2024)

Uncertainty Quantification with the Empirical Neural Tangent Kernel
by: Wilson, Joseph, et al.
Published: (2025)

When Training-Free NAS Meets Vision Transformer: A Neural Tangent Kernel Perspective
by: Zhou, Qiqi, et al.
Published: (2024)

Fast Neural Tangent Kernel Alignment, Norm and Effective Rank via Trace Estimation
by: Hazelden, James
Published: (2025)

MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis
by: Yu, Zixiong, et al.
Published: (2026)

AKBR: Learning Adaptive Kernel-based Representations for Graph Classification
by: Qian, Feifei, et al.
Published: (2024)

Scalable Neural Network Kernels
by: Sehanobish, Arijit, et al.
Published: (2023)

Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients
by: Flügel, Katharina, et al.
Published: (2024)

AscendKernelGen: A Systematic Study of LLM-Based Kernel Generation for Neural Processing Units
by: Cao, Xinzi, et al.
Published: (2026)

Transformer Neural Processes - Kernel Regression
by: Jenson, Daniel, et al.
Published: (2024)

Neural Tangent Knowledge Distillation for Optical Convolutional Networks
by: Xiang, Jinlin, et al.
Published: (2025)

Debiasing Kernel-Based Generative Models
by: Qin, Tian, et al.
Published: (2025)

Applying Ensemble Models based on Graph Neural Network and Reinforcement Learning for Wind Power Forecasting
by: Song, Hongjin, et al.
Published: (2025)

Graph Edit Distance with General Costs Using Neural Set Divergence
by: Jain, Eeshaan, et al.
Published: (2024)

Curvature-Aware PCA with Geodesic Tangent Space Aggregation for Semi-Supervised Learning
by: Levada, Alexandre L. M.
Published: (2026)

Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications
by: Lu, Mingfei, et al.
Published: (2024)

Empirical Validation of the Classification-Verification Dichotomy for AI Safety Gates
by: Scrivens, Arsenios
Published: (2026)

Equivariant Neural Tangent Kernels
by: Misof, Philipp, et al.
Published: (2024)

POCKET: Pruning Random Convolution Kernels for Time Series Classification from a Feature Selection Perspective
by: Chen, Shaowu, et al.
Published: (2023)

Q-function Decomposition with Intervention Semantics with Factored Action Spaces
by: Lee, Junkyu, et al.
Published: (2025)

The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
by: Lim, Derek, et al.
Published: (2024)

How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
by: Choi, Hyeong Kyu, et al.
Published: (2025)

Align Your Tangent: Training Better Consistency Models via Manifold-Aligned Tangents
by: Kim, Beomsu, et al.
Published: (2025)

Learning Molecular Chirality via Chiral Determinant Kernels
by: Shi, Runhan, et al.
Published: (2026)

DPO Kernels: A Semantically-Aware, Kernel-Enhanced, and Divergence-Rich Paradigm for Direct Preference Optimization
by: Das, Amitava, et al.
Published: (2025)

CauScale: Neural Causal Discovery at Scale
by: Peng, Bo, et al.
Published: (2026)

Kernel-Level Energy-Efficient Neural Architecture Search for Tabular Dataset
by: La, Hoang-Loc, et al.
Published: (2025)