IEEE2d
On the Convergence of Decentralized Stochastic Gradient Descent With Biased Gradients
Abstract: Stochastic optimization algorithms are widely used to solve large-scale machine learning problems. However, their theoretical analysis necessitates access to unbiased estimates of the true ...
C&EN18d
Polarization-Independent High-Q Phase Gradient Metasurfaces
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States Department of Chemistry, Washington University in St. Louis, St. Louis, ...
istockphoto20d
Abstract Mash Line and Point Scales on The Dark Gradient Background With Map of Zambia. 3D Mesh Polygonal Network Connections. stock illustration...
Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...
the-decoder24d
The Stargate Project: $500 billion for US AI infrastructure
The first hints about Stargate emerged in March 2024. OpenAI researcher Noam Brown, who works on the company's next-generation o-models, compared the scale of the project to the Apollo program and ...
IEEE26d
Gradient-Guided Local Search for Large-Scale Hypervolume Subset Selection
Thus, an algorithm which can efficiently select a high-quality subset from a large-scale candidate set (e.g., UA) is needed. In this paper, we propose a gradient-guided local search hypervolume subset ...