Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.
CUDA-L2 is a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels. CUDA-L2 ...
Abstract: Deep matrix factorization (DMF) has the capability to discover hierarchical structures within raw data by factorizing matrices layer by layer, allowing it to utilize latent information for ...
General Semi-Nonnegative Matrix Factorization and Its Application for Statistical Process Monitoring
Abstract: As an effective feature extraction and dimensionality reduction technique, nonnegative matrix factorization (NMF) has been widely applied in fault detection in recent years. The requirement ...
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