:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Peiyuan, Karbasi, Amin
Format:	Preprint
Published:	2024
Subjects:	Optimization and Control Machine Learning
Online Access:	https://arxiv.org/abs/2412.08025
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
by: Zhang, Liang, et al.
Published: (2023)

Edge of Stochastic Stability: Revisiting the Edge of Stability for SGD
by: Andreyev, Arseniy, et al.
Published: (2024)

Precise Performance of Linear Denoisers in the Proportional Regime
by: Ghane, Reza, et al.
Published: (2026)

Multivariate Online Linear Regression for Hierarchical Forecasting
by: Hihat, Massil, et al.
Published: (2024)

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes
by: Huo, Dongyan, et al.
Published: (2022)

Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
by: Jung, Hyunji, et al.
Published: (2025)

A Simplified Analysis of SGD for Linear Regression with Weight Averaging
by: Meterez, Alexandru, et al.
Published: (2025)

Non-Euclidean Gradient Descent Operates at the Edge of Stability
by: Islamov, Rustem, et al.
Published: (2026)

Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
by: Zhang, Gavin, et al.
Published: (2025)

Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
by: Tsoy, Nikita, et al.
Published: (2024)

Optimal Cross-Validation for Sparse Linear Regression
by: Cory-Wright, Ryan, et al.
Published: (2023)

What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
by: Bennouna, Omar, et al.
Published: (2025)

Zeroth-Order Optimization at the Edge of Stability
by: Song, Minhak, et al.
Published: (2026)

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
by: Alfano, Carlo, et al.
Published: (2023)

Understanding SGD with Exponential Moving Average: A Case Study in Linear Regression
by: Li, Xuheng, et al.
Published: (2025)

Convergence Rates for Gradient Descent on the Edge of Stability in Overparametrised Least Squares
by: MacDonald, Lachlan Ewen, et al.
Published: (2025)

A Novel Approach in Solving Stochastic Generalized Linear Regression via Nonconvex Programming
by: Anh, Vu Duc, et al.
Published: (2024)

Sample Complexity of Linear Quadratic Regulator Without Initial Stability
by: Moghaddam, Amirreza Neshaei, et al.
Published: (2025)

Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
by: Chakrabarti, Kushal, et al.
Published: (2021)

How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
by: Lai, Kuo-Wei, et al.
Published: (2026)

Implicit Bias of Per-sample Adam on Separable Data: Departure from the Full-batch Regime
by: Baek, Beomhan, et al.
Published: (2025)

Online Control of Linear Systems under Unbounded Noise
by: Ito, Kaito, et al.
Published: (2024)

Faster Convergence of Local SGD for Over-Parameterized Models
by: Qin, Tiancheng, et al.
Published: (2022)

Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime
by: Zhang, Richard Y.
Published: (2021)

Decentralized Sparse Linear Regression via Gradient-Tracking: Linear Convergence and Statistical Guarantees
by: Maros, Marie, et al.
Published: (2022)

Statistical Robustness of Interval CVaR Based Regression Models under Perturbation and Contamination
by: You, Yulei, et al.
Published: (2026)

SGD at the Edge of Stability: The Stochastic Sharpness Gap
by: Liao, Fangshuo, et al.
Published: (2026)

On Linear Convergence of PI Consensus Algorithm under the Restricted Secant Inequality
by: Chakrabarti, Kushal, et al.
Published: (2023)

Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling
by: Rosso, Haley, et al.
Published: (2025)

Towards An Unsupervised Learning Scheme for Efficiently Solving Parameterized Mixed-Integer Programs
by: Qu, Shiyuan, et al.
Published: (2024)

Toward Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixture Models
by: Xu, Weihang, et al.
Published: (2024)

Momentum Further Constrains Sharpness at the Edge of Stochastic Stability
by: Andreyev, Arseniy, et al.
Published: (2026)

A Rod Flow Model for Adam at the Edge of Stability
by: Regis, Eric, et al.
Published: (2026)

FastPart: Over-Parameterized Stochastic Gradient Descent for Sparse optimisation on Measures
by: De Castro, Yohann, et al.
Published: (2023)

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity
by: Wang, Han, et al.
Published: (2023)

Stability of Transformers under Layer Normalization
by: Kan, Kelvin, et al.
Published: (2025)

Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
by: Agrawalla, Bhavya, et al.
Published: (2023)

A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization
by: Luo, Yudong, et al.
Published: (2024)

Combinatorial Sparse PCA Beyond the Spiked Identity Model
by: Kumar, Syamantak, et al.
Published: (2026)

Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation
by: Zhang, Yixuan, et al.
Published: (2024)