From Continual Learning to SGD and Back: Better Rates for Continual Linear Models
Fuente:
arXiv
Saved in:
| Main Authors: | Evron, Itay, Levinstein, Ran, Schliserman, Matan, Sherman, Uri, Koren, Tomer, Soudry, Daniel, Srebro, Nathan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Optimal Rates in Continual Linear Regression via Increasing Regularization
by: Levinstein, Ran, et al.
Published: (2025)
by: Levinstein, Ran, et al.
Published: (2025)
Are Greedy Task Orderings Better Than Random in Continual Linear Regression?
by: Tsipory, Matan, et al.
Published: (2025)
by: Tsipory, Matan, et al.
Published: (2025)
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)
by: Schliserman, Matan, et al.
Published: (2024)
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
by: Attia, Amit, et al.
Published: (2025)
by: Attia, Amit, et al.
Published: (2025)
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)
by: Schliserman, Matan, et al.
Published: (2024)
Optimal L2 Regularization in High-dimensional Continual Linear Regression
by: Karpel, Gilad, et al.
Published: (2026)
by: Karpel, Gilad, et al.
Published: (2026)
Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification
by: Schliserman, Matan, et al.
Published: (2025)
by: Schliserman, Matan, et al.
Published: (2025)
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2025)
by: Schliserman, Matan, et al.
Published: (2025)
Provable Tempered Overfitting of Minimal Nets and Typical Nets
by: Harel, Itamar, et al.
Published: (2024)
by: Harel, Itamar, et al.
Published: (2024)
Rate-Optimal Policy Optimization for Linear Markov Decision Processes
by: Sherman, Uri, et al.
Published: (2023)
by: Sherman, Uri, et al.
Published: (2023)
Convergence and Sample Complexity of First-Order Methods for Agnostic Reinforcement Learning
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting -- An Analytical Model
by: Goldfarb, Daniel, et al.
Published: (2024)
by: Goldfarb, Daniel, et al.
Published: (2024)
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
The Hidden Cost of Approximation in Online Mirror Descent
by: Schlisselberg, Ofir, et al.
Published: (2025)
by: Schlisselberg, Ofir, et al.
Published: (2025)
PLUMAGE: Probabilistic Low rank Unbiased Min Variance Gradient Estimator for Efficient Large Model Training
by: Haroush, Matan, et al.
Published: (2025)
by: Haroush, Matan, et al.
Published: (2025)
Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
by: Harel, Itamar, et al.
Published: (2025)
by: Harel, Itamar, et al.
Published: (2025)
Learning Rate Annealing Improves Tuning Robustness in Stochastic Optimization
by: Attia, Amit, et al.
Published: (2025)
by: Attia, Amit, et al.
Published: (2025)
The Implicit Bias of Gradient Descent on Separable Data
by: Soudry, Daniel, et al.
Published: (2017)
by: Soudry, Daniel, et al.
Published: (2017)
Regret Minimization and Convergence to Equilibria in General-sum Markov Games
by: Erez, Liad, et al.
Published: (2022)
by: Erez, Liad, et al.
Published: (2022)
Exact Mean Square Linear Stability Analysis for SGD
by: Mulayoff, Rotem, et al.
Published: (2023)
by: Mulayoff, Rotem, et al.
Published: (2023)
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
by: Buzaglo, Gon, et al.
Published: (2024)
by: Buzaglo, Gon, et al.
Published: (2024)
Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators
by: Blumenfeld, Yaniv, et al.
Published: (2024)
by: Blumenfeld, Yaniv, et al.
Published: (2024)
From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
by: Erez, Liad, et al.
Published: (2025)
by: Erez, Liad, et al.
Published: (2025)
Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks
by: Kinderman, Edan, et al.
Published: (2024)
by: Kinderman, Edan, et al.
Published: (2024)
Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
by: Chmiel, Brian, et al.
Published: (2022)
by: Chmiel, Brian, et al.
Published: (2022)
Nearly Optimal Sample Complexity for Learning with Label Proportions
by: Busa-Fekete, Robert, et al.
Published: (2025)
by: Busa-Fekete, Robert, et al.
Published: (2025)
Quantifying Overfitting along the Regularization Path for Two-Part-Code MDL in Supervised Classification
by: Zhu, Xiaohan, et al.
Published: (2025)
by: Zhu, Xiaohan, et al.
Published: (2025)
Block Sparse Flash Attention
by: Ohayon, Daniel, et al.
Published: (2025)
by: Ohayon, Daniel, et al.
Published: (2025)
Noisy Interpolation Learning with Shallow Univariate ReLU Networks
by: Joshi, Nirmit, et al.
Published: (2023)
by: Joshi, Nirmit, et al.
Published: (2023)
Tensor-Parallelism with Partially Synchronized Activations
by: Lamprecht, Itay, et al.
Published: (2025)
by: Lamprecht, Itay, et al.
Published: (2025)
How Free is Parameter-Free Stochastic Optimization?
by: Attia, Amit, et al.
Published: (2024)
by: Attia, Amit, et al.
Published: (2024)
Recursive Models for Long-Horizon Reasoning
by: Yang, Chenxiao, et al.
Published: (2026)
by: Yang, Chenxiao, et al.
Published: (2026)
The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication
by: Patel, Kumar Kshitij, et al.
Published: (2024)
by: Patel, Kumar Kshitij, et al.
Published: (2024)
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
by: Joshi, Nirmit, et al.
Published: (2024)
by: Joshi, Nirmit, et al.
Published: (2024)
Fast Rates for Bandit PAC Multiclass Classification
by: Erez, Liad, et al.
Published: (2024)
by: Erez, Liad, et al.
Published: (2024)
A General Reduction for High-Probability Analysis with General Light-Tailed Distributions
by: Attia, Amit, et al.
Published: (2024)
by: Attia, Amit, et al.
Published: (2024)
When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets
by: Zeno, Chen, et al.
Published: (2025)
by: Zeno, Chen, et al.
Published: (2025)
Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back
by: Cohen, Alon, et al.
Published: (2025)
by: Cohen, Alon, et al.
Published: (2025)
Research Program: Theory of Learning in Dynamical Systems
by: Hazan, Elad, et al.
Published: (2025)
by: Hazan, Elad, et al.
Published: (2025)
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
by: Medvedev, Marko, et al.
Published: (2024)
by: Medvedev, Marko, et al.
Published: (2024)
Similar Items
-
Optimal Rates in Continual Linear Regression via Increasing Regularization
by: Levinstein, Ran, et al.
Published: (2025) -
Are Greedy Task Orderings Better Than Random in Continual Linear Regression?
by: Tsipory, Matan, et al.
Published: (2025) -
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024) -
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
by: Attia, Amit, et al.
Published: (2025) -
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)