Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Schliserman, Matan, Koren, Tomer |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2025)
by: Schliserman, Matan, et al.
Published: (2025)
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)
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)
From Continual Learning to SGD and Back: Better Rates for Continual Linear Models
by: Evron, Itay, et al.
Published: (2025)
by: Evron, Itay, et al.
Published: (2025)
Optimal Rates in Continual Linear Regression via Increasing Regularization
by: Levinstein, Ran, et al.
Published: (2025)
by: Levinstein, Ran, et al.
Published: (2025)
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
by: Vansover-Hager, Shira, et al.
Published: (2025)
by: Vansover-Hager, Shira, 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)
Learning Rate Annealing Improves Tuning Robustness in Stochastic Optimization
by: Attia, Amit, et al.
Published: (2025)
by: Attia, Amit, et al.
Published: (2025)
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)
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching
by: Attia, Amit, et al.
Published: (2024)
by: Attia, Amit, 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)
Multiplicative Reweighting for Robust Neural Network Optimization
by: Bar, Noga, et al.
Published: (2021)
by: Bar, Noga, et al.
Published: (2021)
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)
Towards Fully Parameter-Free Stochastic Optimization: Grid Search with Self-Bounding Analysis
by: Zhao, Yuheng, et al.
Published: (2026)
by: Zhao, Yuheng, et al.
Published: (2026)
ContactNet: Geometric-Based Deep Learning Model for Predicting Protein-Protein Interactions
by: Halfon, Matan, et al.
Published: (2024)
by: Halfon, Matan, et al.
Published: (2024)
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
by: Attias, Idan, et al.
Published: (2024)
by: Attias, Idan, et al.
Published: (2024)
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)
by: Livni, Roi
Published: (2024)
The Sample Complexity of Parameter-Free Stochastic Convex Optimization
by: Lawrence, Jared, et al.
Published: (2025)
by: Lawrence, Jared, et al.
Published: (2025)
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
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)
All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension
by: Burla, Tal, et al.
Published: (2026)
by: Burla, Tal, et al.
Published: (2026)
The Hidden Cost of Approximation in Online Mirror Descent
by: Schlisselberg, Ofir, et al.
Published: (2025)
by: Schlisselberg, Ofir, et al.
Published: (2025)
ReHub: Linear Complexity Graph Transformers with Adaptive Hub-Spoke Reassignment
by: Borreda, Tomer, et al.
Published: (2024)
by: Borreda, Tomer, et al.
Published: (2024)
Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back
by: Cohen, Alon, et al.
Published: (2025)
by: Cohen, Alon, et al.
Published: (2025)
On Traceability in $\ell_p$ Stochastic Convex Optimization
by: Voitovych, Sasha, et al.
Published: (2025)
by: Voitovych, Sasha, et al.
Published: (2025)
Enhancing Parallelism in Decentralized Stochastic Convex Optimization
by: Eisen, Ofri, et al.
Published: (2025)
by: Eisen, Ofri, et al.
Published: (2025)
The Sample Complexity of Multiclass and Sparse Contextual Bandits
by: Erez, Liad, et al.
Published: (2026)
by: Erez, Liad, et al.
Published: (2026)
The Price of Adaptivity in Stochastic Convex Optimization
by: Carmon, Yair, et al.
Published: (2024)
by: Carmon, Yair, et al.
Published: (2024)
Stochastic Difference-of-Convex Optimization with Momentum
by: Chayti, El Mahdi, et al.
Published: (2025)
by: Chayti, El Mahdi, et al.
Published: (2025)
Coherence Awareness in Diffractive Neural Networks
by: Kleiner, Matan, et al.
Published: (2024)
by: Kleiner, Matan, et al.
Published: (2024)
Illumination Angular Spectrum Encoding for Controlling the Functionality of Diffractive Networks
by: Kleiner, Matan, et al.
Published: (2026)
by: Kleiner, Matan, et al.
Published: (2026)
Cost-Aware Learning
by: Mohri, Clara, et al.
Published: (2026)
by: Mohri, Clara, et al.
Published: (2026)
Optimal Learning from Label Proportions with General Loss Functions
by: Applebaum, Lorne, et al.
Published: (2025)
by: Applebaum, Lorne, et al.
Published: (2025)
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models
by: Kulikov, Vladimir, et al.
Published: (2024)
by: Kulikov, Vladimir, et al.
Published: (2024)
Exact Mean Square Linear Stability Analysis for SGD
by: Mulayoff, Rotem, et al.
Published: (2023)
by: Mulayoff, Rotem, et al.
Published: (2023)
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity
by: Gao, Wenzhi, et al.
Published: (2024)
by: Gao, Wenzhi, et al.
Published: (2024)
Online Non-Stationary Stochastic Quasar-Convex Optimization
by: Pun, Yuen-Man, et al.
Published: (2024)
by: Pun, Yuen-Man, et al.
Published: (2024)
Similar Items
-
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024) -
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2025) -
Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification
by: Schliserman, Matan, et al.
Published: (2025) -
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
by: Attia, Amit, et al.
Published: (2025) -
From Continual Learning to SGD and Back: Better Rates for Continual Linear Models
by: Evron, Itay, et al.
Published: (2025)