Research Reveals the Optimal Way to Optimize

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...
Nieman Journalism Lab

Want to fight misinformation? Teach people how algorithms work

In an era dominated by social media, misinformation has become an all too familiar foe, infiltrating our feeds and sowing seeds of doubt and confusion. With more than half of social media users across ...
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Deep Learning Optimization — All The Major Optimizers Explained

From SGD to Adam, this guide explains how optimizers work and when to use each one. #Optimizers #DeepLearningTips #AITraining Trump announces two new national holidays, including one on Veterans Day ...
Frontiers

Federated learning-based multimodal approach for early detection and personalized care in cardiac disease

Introduction: Heart disease remains a leading cause of mortality globally, and early detection is critical for effective treatment and management. However, current diagnostic techniques often suffer ...
Frontiers

VHRTrees: a new benchmark dataset for tree detection in satellite imagery and performance evaluation with YOLO-based models

Natural and planted forests, covering approximately 31% of the Earth’s land area, are crucial for global ecosystems, providing essential services such as regulating the water cycle, soil conservation, ...
marktechpost

Eliminating Fixed Learning Rate Schedules in Machine Learning: How Schedule-Free AdamW Optimizer Achieves Superior Accuracy and Efficiency Across Diverse Applications

Optimization theory has emerged as an essential field within machine learning, providing precise frameworks for adjusting model parameters efficiently to achieve accurate learning outcomes. This ...
Scientific Research Publishing

Smith, L. and Topin, N. (2024) Beyond SGD: An Empirical Study of Modern Optimization Techniques in Deep Learning. Journal of Machine Learning Research, 25, 1-20.

ABSTRACT: In the evolving landscape of artificial intelligence and machine learning, the choice of optimization algorithm can significantly impact the success of model training and the accuracy of ...
marktechpost

Unraveling Transformer Optimization: A Hessian-Based Explanation for Adam’s Superiority over SGD

Large Language Models (LLMs) based on Transformer architectures have revolutionized AI development. However, the complexity of their training process remains poorly understood. A significant challenge ...
Scientific Research Publishing

A Comparative Study of Optimization Techniques on the Rosenbrock Function ()

1 Department of Mathematics, University of Ndjamena, Ndjamena, Tchad. 2 Department of Mathematics and Computer Science, University of Cheikh. A. Diop, Dakar, Senegal. In the evolving landscape of ...