A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

Abstract: Support Vector Machines (SVMs) are powerful supervised learning algorithms that are extensively used for both classification and regression tasks. An important component of SVMs is the ...

When Valve announced its upcoming Steam Machine hardware last month, some eagle-eyed gamers may have been surprised to see that the official spec sheet lists support for HDMI 2.0 output, rather than ...

Introduction: This study systematically investigated the relationship between body mass index (BMI) and lung function, incorporating Z-scores, thereby offering a novel approach to lung function ...

ABSTRACT: Support vector machines are recognized as a powerful tool for supervised analysis and classification in different fields, particularly geophysics. In summary, SVMs are binary classifiers.

Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...

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A new study offers insight into the health and lifestyle indicators - including diet, physical activity and weight - that align most closely with healthy brain function across the lifespan. The study ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

ABSTRACT: Background and Theoretical Dilemma: The United States of America (USA) is the world’s largest consumer of crude oil in the world. Ensuring the sustainability of the role of crude oil in the ...