Focal loss
Focal loss is a loss function that reshapes standard cross-entropy loss by adding a (1 - p_t)^gamma modulating factor, which down-weights well-classified (easy) examples so that training concentrates on hard
Training & Optimization
Explore Training & Optimization through related topics and the articles other pages reference most.
Explore articles
Browse subtopics: Computer Vision
Articles that also belong to these categories. Counts cover all of Training & Optimization.
All articles (145)Machine Learning (70)Deep Learning (41)Large Language Models (18)AI Infrastructure (9)Mathematics (9)AI Inference (8)Reinforcement Learning (8)AI Alignment (7)Developer Tools (7)Natural Language Processing (7)Open Source AI (7)MLOps (6)Statistics (6)NVIDIA (4)AI Hardware (3)Artificial Intelligence (3)Computer Vision (3)Reasoning Models (3)Algorithms (2)Chinese AI (2)Data & Datasets (2)Generative AI (2)Meta AI (2)Model Evaluation (2)Robotics (2)Transformer Models (2)AI Agents (1)AI Code Generation (1)AI Models (1)AI Research (1)AI Tools & Products (1)Enterprise AI (1)Google (1)Google DeepMind (1)Humanoid Robots (1)Microsoft (1)Mixture of Experts (1)Model Architecture (1)Neural Networks (1)OpenAI (1)Small Language Models (1)World Models (1)
Showing 1-3 of 3 articles
Masked autoencoder (MAE)
Masked autoencoder (MAE) is a self-supervised learning method for vision transformers that masks roughly 75% of an input image's patches and trains a network to reconstruct the missing pixels from the small…
Pre-training
Pre-training is a stage of machine learning in which a model learns parameters from a source dataset or source objective before those parameters are reused or adapted for a target use.