Imagen de Portada

The Geometric Cost of Normalization: Affine Bounds on the Bayesian Complexity of Neural Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Chun, Sungbae
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Information Theory
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Information-Theoretic Generalization Bounds for Deep Neural Networks
por: He, Haiyun, et al.
Publicado: (2024)

Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning
por: Jamoussi, Nour, et al.
Publicado: (2025)

A DPI-PAC-Bayesian Framework for Generalization Bounds
por: Guan, Muhan, et al.
Publicado: (2025)

Sparse Max-Affine Regression
por: Kanj, Haitham, et al.
Publicado: (2024)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
por: Tran-The, Hung, et al.
Publicado: (2020)

Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural Networks
por: Liu, Suqi, et al.
Publicado: (2024)

Generalization Bounds for Neural Belief Propagation Decoders
por: Adiga, Sudarshan, et al.
Publicado: (2023)

Towards A Unified PAC-Bayesian Framework for Norm-based Generalization Bounds
por: Yi, Xinping, et al.
Publicado: (2026)

Neural Weight Norm = Kolmogorov Complexity
por: Musat, Tiberiu
Publicado: (2026)

A Neural Network Algorithm for KL Divergence Estimation with Quantitative Error Bounds
por: Foss, Mikil, et al.
Publicado: (2025)

Tight Regret Bounds for Bayesian Optimization in One Dimension
por: Scarlett, Jonathan
Publicado: (2018)

Information-Geometric Barycenters for Bayesian Federated Learning
por: Jamoussi, Nour, et al.
Publicado: (2024)

Frame Quantization of Neural Networks
por: Czaja, Wojciech, et al.
Publicado: (2024)

New Bounds on Quantum Sample Complexity of Measurement Classes
por: Heidari, Mohsen, et al.
Publicado: (2024)

Topological Neural Networks over the Air
por: Fiorellino, Simone, et al.
Publicado: (2025)

Klein Model for Hyperbolic Neural Networks
por: Mao, Yidan, et al.
Publicado: (2024)

Graph Attention Network for Node Regression on Random Geometric Graphs with Erdős--Rényi contamination
por: Laha, Somak, et al.
Publicado: (2026)

On Cost-Aware Sequential Hypothesis Testing with Random Costs and Action Cancellation
por: Vershinin, George, et al.
Publicado: (2025)

Transfer Entropy in Graph Convolutional Neural Networks
por: Moldovan, Adrian, et al.
Publicado: (2024)

Mutual Information Estimation via Normalizing Flows
por: Butakov, Ivan, et al.
Publicado: (2024)

On the Theory of Continual Learning with Gradient Descent for Neural Networks
por: Taheri, Hossein, et al.
Publicado: (2025)

Implicit Hypothesis Testing and Divergence Preservation in Neural Network Representations
por: Aksoy, Kadircan, et al.
Publicado: (2026)

Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks
por: Zhang, Shihao, et al.
Publicado: (2025)

Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
por: Taheri, Hossein, et al.
Publicado: (2024)

Generalization Error of Graph Neural Networks in the Mean-field Regime
por: Aminian, Gholamali, et al.
Publicado: (2024)

Minimal Communication-Cost Statistical Learning
por: Sefidgaran, Milad, et al.
Publicado: (2024)

Learning to Compress: Local Rank and Information Compression in Deep Neural Networks
por: Patel, Niket, et al.
Publicado: (2024)

Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks
por: Faramarzi, Sajad, et al.
Publicado: (2024)

Generalization Bounds for Transformer Channel Decoders
por: Zhang, Qinshan, et al.
Publicado: (2026)

Interpretive Efficiency: Information-Geometric Foundations of Data Usefulness
por: Katende, Ronald
Publicado: (2025)

Comparing Comparators in Generalization Bounds
por: Hellström, Fredrik, et al.
Publicado: (2023)

Cost-Aware Optimal Pairwise Pure Exploration
por: Wu, Di, et al.
Publicado: (2025)

Foundation of Calculating Normalized Maximum Likelihood for Continuous Probability Models
por: Suzuki, Atsushi, et al.
Publicado: (2024)

The No-Clash Teaching Dimension is Bounded by VC Dimension
por: Liu, Jiahua, et al.
Publicado: (2026)

Block-Sample MAC-Bayes Generalization Bounds
por: Frey, Matthias, et al.
Publicado: (2026)

Generalization Bounds via Conditional $f$-Information
por: Wang, Ziqiao, et al.
Publicado: (2024)

Lower Bounds for Time-Varying Kernelized Bandits
por: Cai, Xu, et al.
Publicado: (2024)

Matrix Completion in Group Testing: Bounds and Simulations
por: Tran, Trung-Khang, et al.
Publicado: (2025)

Improved Sample Complexity Bounds for Diffusion Model Training
por: Gupta, Shivam, et al.
Publicado: (2023)

eOptShrinkQ: Near-Lossless KV Cache Compression Through Optimal Spectral Denoising and Quantization
por: Su, Pei-Chun
Publicado: (2026)