Early Stopping
Description
Early Stopping is a regularization technique for deep neural networks that stops training when parameter updates no longer begin to yield improves on a validation set. In essence, we store and update the current best parameters during training, and when parameter updates no longer yield an improvement (after a set number of iterations) we stop training and use the last best parameters. It works as a regularizer by restricting the optimization procedure to a smaller volume of parameter space.
Image Source: Ramazan Gençay
Papers Using This Method
Some remarks on gradient dominance and LQR policy optimization2025-07-14Chat-Ghosting: A Comparative Study of Methods for Auto-Completion in Dialog Systems2025-07-08Early Stopping Tabular In-Context Learning2025-06-26Less is More: Undertraining Experts Improves Model Upcycling2025-06-17Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity2025-06-03Generalization Dynamics of Linear Diffusion Models2025-05-30Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion2025-05-30From Token to Action: State Machine Reasoning to Mitigate Overthinking in Information Retrieval2025-05-29Deep Spectral Prior2025-05-26On the Role of Label Noise in the Feature Learning Process2025-05-25First Finish Search: Efficient Test-Time Scaling in Large Language Models2025-05-23Bigger Isn't Always Memorizing: Early Stopping Overparameterized Diffusion Models2025-05-22Thinking Short and Right Over Thinking Long: Serving LLM Reasoning Efficiently and Accurately2025-05-19Approximation and Generalization Abilities of Score-based Neural Network Generative Models for Sub-Gaussian Distributions2025-05-16Multimodal Sentiment Analysis on CMU-MOSEI Dataset using Transformer-based Models2025-05-09Precise gradient descent training dynamics for finite-width multi-layer neural networks2025-05-08ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning2025-05-08Circinus: Efficient Query Planner for Compound ML Serving2025-04-23TD-Suite: All Batteries Included Framework for Technical Debt Classification2025-04-15Adaptive Low Light Enhancement via Joint Global-Local Illumination Adjustment2025-04-01