Cover Image

Minor First, Major Last: A Depth-Induced Implicit Bias of Sharpness-Aware Minimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Moon, Chaewon, Si, Dongkuk, Yun, Chulhee
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Cost of Robustness: Tighter Bounds on Parameter Complexity for Robust Memorization in ReLU Nets
by: Kim, Yujun, et al.
Published: (2025)

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

Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness
by: Shin, Baekrok, et al.
Published: (2026)

Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models
by: Cao, Tianxiao, et al.
Published: (2025)

Provable Benefit of Cutout and CutMix for Feature Learning
by: Oh, Junsoo, et al.
Published: (2024)

Stability Analysis of Sharpness-Aware Minimization
by: Kim, Hoki, et al.
Published: (2023)

Navigating Potholes with Geometry-Aware Sharpness Minimization
by: Dufort-Labbé, Simon, et al.
Published: (2026)

Membership Privacy Risks of Sharpness Aware Minimization
by: Kim, Young In, et al.
Published: (2023)

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization
by: Tan, Chengli, et al.
Published: (2025)

Revisiting Sharpness-Aware Minimization: A More Faithful and Effective Implementation
by: Chen, Jianlong, et al.
Published: (2026)

SAMOSA: Sharpness Aware Minimization for Open Set Active learning
by: Kim, Young In, et al.
Published: (2025)

Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count
by: Cho, Hanseul, et al.
Published: (2024)

DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity
by: Shin, Baekrok, et al.
Published: (2024)

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
by: Cho, Yeseul, et al.
Published: (2025)

Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?
by: Kim, Jihwan, et al.
Published: (2026)

X-SAM: Boosting Sharpness-Aware Minimization with Dominant-Eigenvector Gradient Correction
by: Duan, Hongru, et al.
Published: (2026)

Sharpness-Aware Minimization in Logit Space Efficiently Enhances Direct Preference Optimization
by: Luo, Haocheng, et al.
Published: (2026)

FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization
by: Dai, Yucong, et al.
Published: (2025)

Towards Understanding the Role of Sharpness-Aware Minimization Algorithms for Out-of-Distribution Generalization
by: Schapiro, Samuel, et al.
Published: (2024)

Attributing Data for Sharpness-Aware Minimization
by: Ren, Chenyang, et al.
Published: (2025)

Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification
by: Luo, Yihong, et al.
Published: (2024)

Sharpness-Aware Minimization with Z-Score Gradient Filtering
by: Yun, Vincent-Daniel
Published: (2025)

Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
by: Kim, Hyunsu, et al.
Published: (2025)

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

Gradient Compression May Hurt Generalization: A Remedy by Synthetic Data Guided Sharpness Aware Minimization
by: Gu, Yujie, et al.
Published: (2026)

Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models
by: Liu, Yuhang, et al.
Published: (2025)

Enhancing Robustness of Offline Reinforcement Learning Under Data Corruption via Sharpness-Aware Minimization
by: Xu, Le, et al.
Published: (2025)

Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More
by: Yoo, Geonhui, et al.
Published: (2025)

Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training
by: Song, Minhak, et al.
Published: (2025)

On the Duality Between Sharpness-Aware Minimization and Adversarial Training
by: Zhang, Yihao, et al.
Published: (2024)

Stabilizing Sharpness-aware Minimization Through A Simple Renormalization Strategy
by: Tan, Chengli, et al.
Published: (2024)

Sharpness-Aware Teleportation on Riemannian Manifolds
by: Truong, Tuan, et al.
Published: (2023)

Sharpness-Aware Black-Box Optimization
by: Ye, Feiyang, et al.
Published: (2024)

Locality-Aware Redundancy Pruning for LLM Depth Compression
by: Yun, Vincent-Daniel, et al.
Published: (2026)

Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling
by: Xu, Jian, et al.
Published: (2024)

Disentangling Granularity: An Implicit Inductive Bias in Factorized VAEs
by: Chen, Zihao, et al.
Published: (2025)

Correcting Performance Estimation Bias in Imbalanced Classification with Minority Subconcepts
by: Maxson, Taylor, et al.
Published: (2026)

Implicit Bias of the JKO Scheme
by: Halmos, Peter, et al.
Published: (2025)

NCSAM Noise-Compensated Sharpness-Aware Minimization for Noisy Label Learning
by: Xu, Jiayu, et al.
Published: (2026)

Tractable Sharpness-Aware Learning of Probabilistic Circuits
by: Suresh, Hrithik, et al.
Published: (2025)