This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with.

Abstract: The problem of learning a channel decoder is considered for two channel models. The first model is an additive noise channel whose noise distribution is unknown and nonparametric. The ...

Breast cancer diagnosis relies on imaging, yet conventional Doppler ultrasound possesses limitations in visualizing tumor microvasculature. This study aimed to compare Microvascular Flow imaging ...

The spatial organization of chromatophore-muscle innervation by motoneurons enables the generation of chromatophore-shaped noise, virtual or composite chromatophores, and shape elements such as lines ...

Abstract: Medical practice for determining haemoglobin (Hb) concentration, which is important for anemic patients in need of blood transfusion, requires a blood sample. In this paper, we propose a non ...

Yann LeCun (Courant Institute, NYU) and Corinna Cortes (Google Labs, New York) hold the copyright of MNIST dataset, which is a derivative work from the original NIST datasets. The MNIST database of ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

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For example, AI applications to medical diagnosis should be regulated very differently from AI applications to self-driving cars. U.S. National Academies report on AI and the Future of Work, study ...

This webpage is a benchmark data set for keystroke dynamics. It is a supplement to the paper "Comparing Anomaly-Detection Algorithms for Keystroke Dynamics," by Kevin Killourhy and Roy Maxion, ...

The Normalised Difference Vegetation Index (NDVI) grids and maps are derived from satellite data. The data provides an overview of the status and dynamics of vegetation across Australia, providing a ...