Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression ...

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 ...

In this article, we develop piecewise linear surrogates using Machine Learning (ML) models and the Optimization and Machine Learning Toolkit (OMLT) to show how process families can be designed to ...

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality ...

In this paper, we propose a novel approach called the Partially-Supervised Graph Derivation Network with Meta Learning (PS-GDNML) for time series anomaly detection. PS-GDNML combines the power of ...

Federated Learning offers a solution for collaborative training without centralized storage. Nonetheless, it often overlooks the issue of data heterogeneity across sites. We propose a Federated Graph ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

A linear SVR model uses an unusual error/loss function and cannot be trained using standard simple techniques, and so evolutionary optimization training is used. The goal of a machine learning ...