A Theoretical Analysis of Noise Geometry in Stochastic Gradient Descent
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Mingze, Wu, Lei |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2024)
by: Ziyin, Liu, et al.
Published: (2024)
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent with Predictable Virtual Noise
by: Partohaghighi, Mohammad
Published: (2026)
by: Partohaghighi, Mohammad
Published: (2026)
Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent
by: Sato, Naoki, et al.
Published: (2024)
by: Sato, Naoki, et al.
Published: (2024)
Noise Balance and Stationary Distribution of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2023)
by: Ziyin, Liu, et al.
Published: (2023)
Stochastic Gradient Descent with Momentum is Algorithmically Stable
by: Lei, Yunwen, et al.
Published: (2026)
by: Lei, Yunwen, et al.
Published: (2026)
Stochastic Gradient Descent for Two-layer Neural Networks
by: Cao, Dinghao, et al.
Published: (2024)
by: Cao, Dinghao, et al.
Published: (2024)
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent
by: Vaswani, Sharan, et al.
Published: (2021)
by: Vaswani, Sharan, et al.
Published: (2021)
Adjacent Leader Decentralized Stochastic Gradient Descent
by: He, Haoze, et al.
Published: (2024)
by: He, Haoze, et al.
Published: (2024)
Stochastic Adaptive Gradient Descent Without Descent
by: Aujol, Jean-François, et al.
Published: (2025)
by: Aujol, Jean-François, et al.
Published: (2025)
On the Generalization of Stochastic Gradient Descent with Momentum
by: Ramezani-Kebrya, Ali, et al.
Published: (2018)
by: Ramezani-Kebrya, Ali, et al.
Published: (2018)
A Bootstrap Perspective on Stochastic Gradient Descent
by: Lan, Hongjian, et al.
Published: (2025)
by: Lan, Hongjian, et al.
Published: (2025)
Statistical Guarantees for High-Dimensional Stochastic Gradient Descent
by: Li, Jiaqi, et al.
Published: (2025)
by: Li, Jiaqi, et al.
Published: (2025)
DOME: Improving Signal-to-Noise in Stochastic Gradient Descent via Sharp-Direction Subspace Filtering
by: Nicolas, Julien, et al.
Published: (2025)
by: Nicolas, Julien, et al.
Published: (2025)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023)
by: Li, Tianyou, et al.
Published: (2023)
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
by: Dang, Thanh, et al.
Published: (2025)
by: Dang, Thanh, et al.
Published: (2025)
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality
by: Wei, Ziyang, et al.
Published: (2023)
by: Wei, Ziyang, et al.
Published: (2023)
A Unified Analysis of Stochastic Gradient Descent with Arbitrary Data Permutations and Beyond
by: Li, Yipeng, et al.
Published: (2025)
by: Li, Yipeng, et al.
Published: (2025)
Central Limit Theorems for Stochastic Gradient Descent Quantile Estimators
by: Wei, Ziyang, et al.
Published: (2025)
by: Wei, Ziyang, et al.
Published: (2025)
Stochastic Gradient Descent for Nonparametric Additive Regression
by: Chen, Xin, et al.
Published: (2024)
by: Chen, Xin, et al.
Published: (2024)
Bolstering Stochastic Gradient Descent with Model Building
by: Birbil, S. Ilker, et al.
Published: (2021)
by: Birbil, S. Ilker, et al.
Published: (2021)
Descend or Rewind? Stochastic Gradient Descent Unlearning
by: Mu, Siqiao, et al.
Published: (2025)
by: Mu, Siqiao, et al.
Published: (2025)
Stochastic Normalized Gradient Descent with Momentum for Large-Batch Training
by: Zhao, Shen-Yi, et al.
Published: (2020)
by: Zhao, Shen-Yi, et al.
Published: (2020)
Cheap Bootstrap for Fast Uncertainty Quantification of Stochastic Gradient Descent
by: Lam, Henry, et al.
Published: (2023)
by: Lam, Henry, et al.
Published: (2023)
Stochastic Gradient Descent with Adaptive Data
by: Che, Ethan, et al.
Published: (2024)
by: Che, Ethan, et al.
Published: (2024)
Stochastic Gradient Descent with Strategic Querying
by: Jiang, Nanfei, et al.
Published: (2025)
by: Jiang, Nanfei, et al.
Published: (2025)
Learning Operators with Stochastic Gradient Descent in General Hilbert Spaces
by: Shi, Lei, et al.
Published: (2024)
by: Shi, Lei, et al.
Published: (2024)
Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees
by: Armacki, Aleksandar, et al.
Published: (2024)
by: Armacki, Aleksandar, et al.
Published: (2024)
Generalization Bounds of Stochastic Gradient Descent in Homogeneous Neural Networks
by: Ma, Wenquan, et al.
Published: (2026)
by: Ma, Wenquan, et al.
Published: (2026)
Stochastic Gradient Descent for Gaussian Processes Done Right
by: Lin, Jihao Andreas, et al.
Published: (2023)
by: Lin, Jihao Andreas, et al.
Published: (2023)
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent
by: Deng, Xiaoge, et al.
Published: (2023)
by: Deng, Xiaoge, et al.
Published: (2023)
Personalized Federated Learning with Exact Stochastic Gradient Descent
by: Nikoloutsopoulos, Sotirios, et al.
Published: (2022)
by: Nikoloutsopoulos, Sotirios, et al.
Published: (2022)
Variational Stochastic Gradient Descent for Deep Neural Networks
by: Chen, Haotian, et al.
Published: (2024)
by: Chen, Haotian, et al.
Published: (2024)
Towards Learning Stochastic Population Models by Gradient Descent
by: Kreikemeyer, Justin N., et al.
Published: (2024)
by: Kreikemeyer, Justin N., et al.
Published: (2024)
Learning Curves of Stochastic Gradient Descent in Kernel Regression
by: Zhang, Haihan, et al.
Published: (2025)
by: Zhang, Haihan, et al.
Published: (2025)
An ADRC-Incorporated Stochastic Gradient Descent Algorithm for Latent Factor Analysis
by: Li, Jinli, et al.
Published: (2024)
by: Li, Jinli, et al.
Published: (2024)
Learning Operators by Regularized Stochastic Gradient Descent with Operator-valued Kernels
by: Yang, Jia-Qi, et al.
Published: (2025)
by: Yang, Jia-Qi, et al.
Published: (2025)
Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
by: Naganuma, Hiroki, et al.
Published: (2026)
by: Naganuma, Hiroki, et al.
Published: (2026)
Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction
by: Wei, Ziyang, et al.
Published: (2026)
by: Wei, Ziyang, et al.
Published: (2026)
Adaptive Heavy-Tailed Stochastic Gradient Descent
by: Gong, Bodu, et al.
Published: (2025)
by: Gong, Bodu, et al.
Published: (2025)
Streaming Krylov-Accelerated Stochastic Gradient Descent
by: Thomas, Stephen
Published: (2025)
by: Thomas, Stephen
Published: (2025)
Similar Items
-
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2024) -
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent with Predictable Virtual Noise
by: Partohaghighi, Mohammad
Published: (2026) -
Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent
by: Sato, Naoki, et al.
Published: (2024) -
Noise Balance and Stationary Distribution of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2023) -
Stochastic Gradient Descent with Momentum is Algorithmically Stable
by: Lei, Yunwen, et al.
Published: (2026)