Information-Theoretic Generalization Bounds for Deep Neural Networks
Fuente:
arXiv
Guardado en:
| Autores principales: | He, Haiyun, Goldfeld, Ziv |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
On the Generalization of Knowledge Distillation: An Information-Theoretic View
por: Li, Bingying, et al.
Publicado: (2026)
por: Li, Bingying, et al.
Publicado: (2026)
Performance Guarantees for Quantum Neural Estimation of Entropies
por: Sreekumar, Sreejith, et al.
Publicado: (2025)
por: Sreekumar, Sreejith, et al.
Publicado: (2025)
Learning to Compress: Local Rank and Information Compression in Deep Neural Networks
por: Patel, Niket, et al.
Publicado: (2024)
por: Patel, Niket, et al.
Publicado: (2024)
Pufferfish Privacy: An Information-Theoretic Study
por: Nuradha, Theshani, et al.
Publicado: (2022)
por: Nuradha, Theshani, et al.
Publicado: (2022)
Quantum Neural Estimation of Entropies
por: Goldfeld, Ziv, et al.
Publicado: (2023)
por: Goldfeld, Ziv, et al.
Publicado: (2023)
Quantum Pufferfish Privacy: A Flexible Privacy Framework for Quantum Systems
por: Nuradha, Theshani, et al.
Publicado: (2023)
por: Nuradha, Theshani, et al.
Publicado: (2023)
Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning
por: Barnes, L. P., et al.
Publicado: (2022)
por: Barnes, L. P., et al.
Publicado: (2022)
Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks
por: Zhang, Shihao, et al.
Publicado: (2025)
por: Zhang, Shihao, et al.
Publicado: (2025)
Estimation of Stochastic Optimal Transport Maps
por: Nietert, Sloan, et al.
Publicado: (2025)
por: Nietert, Sloan, et al.
Publicado: (2025)
Neural Polar Decoders for DNA Data Storage
por: Aharoni, Ziv, et al.
Publicado: (2025)
por: Aharoni, Ziv, et al.
Publicado: (2025)
Tighter Information-Theoretic Generalization Bounds via a Novel Class of Change of Measure Inequalities
por: Liu, Yanxiao, et al.
Publicado: (2026)
por: Liu, Yanxiao, et al.
Publicado: (2026)
Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
por: He, Haiyun, et al.
Publicado: (2024)
por: He, Haiyun, et al.
Publicado: (2024)
Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality
por: Bongole, Raghav, et al.
Publicado: (2024)
por: Bongole, Raghav, et al.
Publicado: (2024)
Neural Networks Learn Generic Multi-Index Models Near Information-Theoretic Limit
por: Zhang, Bohan, et al.
Publicado: (2025)
por: Zhang, Bohan, et al.
Publicado: (2025)
Neural Polar Decoders for Deletion Channels
por: Aharoni, Ziv, et al.
Publicado: (2025)
por: Aharoni, Ziv, et al.
Publicado: (2025)
Robust Estimation under the Wasserstein Distance
por: Nietert, Sloan, et al.
Publicado: (2023)
por: Nietert, Sloan, et al.
Publicado: (2023)
Robust Alignment via Partial Gromov-Wasserstein Distances
por: Gong, Xiaoyun, et al.
Publicado: (2025)
por: Gong, Xiaoyun, et al.
Publicado: (2025)
Generalization Bounds for Neural Belief Propagation Decoders
por: Adiga, Sudarshan, et al.
Publicado: (2023)
por: Adiga, Sudarshan, et al.
Publicado: (2023)
On the Generalization for Transfer Learning: An Information-Theoretic Analysis
por: Wu, Xuetong, et al.
Publicado: (2022)
por: Wu, Xuetong, et al.
Publicado: (2022)
Code Rate Optimization via Neural Polar Decoders
por: Aharoni, Ziv, et al.
Publicado: (2025)
por: Aharoni, Ziv, et al.
Publicado: (2025)
Generalization Bounds via Conditional $f$-Information
por: Wang, Ziqiao, et al.
Publicado: (2024)
por: Wang, Ziqiao, et al.
Publicado: (2024)
Distributional Information Embedding: A Framework for Multi-bit Watermarking
por: He, Haiyun, et al.
Publicado: (2025)
por: He, Haiyun, et al.
Publicado: (2025)
The Geometric Cost of Normalization: Affine Bounds on the Bayesian Complexity of Neural Networks
por: Chun, Sungbae
Publicado: (2026)
por: Chun, Sungbae
Publicado: (2026)
Fast Rate Information-theoretic Bounds on Generalization Errors
por: Wu, Xuetong, et al.
Publicado: (2023)
por: Wu, Xuetong, et al.
Publicado: (2023)
Generalization Error of Graph Neural Networks in the Mean-field Regime
por: Aminian, Gholamali, et al.
Publicado: (2024)
por: Aminian, Gholamali, et al.
Publicado: (2024)
Information-Theoretic Generative Clustering of Documents
por: Du, Xin, et al.
Publicado: (2024)
por: Du, Xin, et al.
Publicado: (2024)
Information-Theoretic Discrete Diffusion
por: Jeon, Moongyu, et al.
Publicado: (2025)
por: Jeon, Moongyu, et al.
Publicado: (2025)
Bounds on the Excess Minimum Risk via Generalized Information Divergence Measures
por: Omanwar, Ananya, et al.
Publicado: (2025)
por: Omanwar, Ananya, et al.
Publicado: (2025)
An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics
por: Liu, Wenliang, et al.
Publicado: (2024)
por: Liu, Wenliang, et al.
Publicado: (2024)
An Information Theoretic Perspective on Conformal Prediction
por: Correia, Alvaro H. C., et al.
Publicado: (2024)
por: Correia, Alvaro H. C., et al.
Publicado: (2024)
An Information-Theoretic Analysis of Temporal GNNs
por: Farzaneh, Amirmohammad
Publicado: (2024)
por: Farzaneh, Amirmohammad
Publicado: (2024)
An Information-Theoretic Analysis of In-Context Learning
por: Jeon, Hong Jun, et al.
Publicado: (2024)
por: Jeon, Hong Jun, et al.
Publicado: (2024)
Information-Theoretic Proofs for Diffusion Sampling
por: Reeves, Galen, et al.
Publicado: (2025)
por: Reeves, Galen, et al.
Publicado: (2025)
Information Theoretic Perspective on Representation Learning
por: Pereg, Deborah, et al.
Publicado: (2026)
por: Pereg, Deborah, et al.
Publicado: (2026)
A Generalized Information Bottleneck Theory of Deep Learning
por: Westphal, Charles, et al.
Publicado: (2025)
por: Westphal, Charles, et al.
Publicado: (2025)
Directed Information $γ$-covering: An Information-Theoretic Framework for Context Engineering
por: Huang, Hai
Publicado: (2025)
por: Huang, Hai
Publicado: (2025)
A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions
por: Makkeh, Abdullah, et al.
Publicado: (2023)
por: Makkeh, Abdullah, et al.
Publicado: (2023)
Information-Theoretic Measures on Lattices for High-Order Interactions
por: Liu, Zhaolu, et al.
Publicado: (2024)
por: Liu, Zhaolu, et al.
Publicado: (2024)
Information-Theoretic Framework for Understanding Modern Machine-Learning
por: Feder, Meir, et al.
Publicado: (2025)
por: Feder, Meir, et al.
Publicado: (2025)
Information Theoretic Learning for Diffusion Models with Warm Start
por: Shen, Yirong, et al.
Publicado: (2025)
por: Shen, Yirong, et al.
Publicado: (2025)
Ejemplares similares
-
On the Generalization of Knowledge Distillation: An Information-Theoretic View
por: Li, Bingying, et al.
Publicado: (2026) -
Performance Guarantees for Quantum Neural Estimation of Entropies
por: Sreekumar, Sreejith, et al.
Publicado: (2025) -
Learning to Compress: Local Rank and Information Compression in Deep Neural Networks
por: Patel, Niket, et al.
Publicado: (2024) -
Pufferfish Privacy: An Information-Theoretic Study
por: Nuradha, Theshani, et al.
Publicado: (2022) -
Quantum Neural Estimation of Entropies
por: Goldfeld, Ziv, et al.
Publicado: (2023)