Visual Studio Magazine

Data Anomaly Detection Using LightGBM

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...
EurekAlert!

Serial-autoencoder for personalized recommendation

In the last decade, auxiliary information has been widely used to address data sparsity. Due to the advantages of feature extraction and the no-label requirement, autoencoder-based methods addressing ...
insideHPC

Research Highlights: MIT Develops First Generative Model for Anomaly Detection that Combines both Reconstruction-based and Prediction-based Models

Kalyan Veeramachaneni and his team at the MIT Data-to-AI (DAI) Lab have developed the first generative model, the AutoEncoder with Regression (AER) for time series anomaly detection, that combines ...
EurekAlert!

An approach for unsupervised domain adaptation based on integrated autoencoder

Unsupervised domain adaptation has provoked vast amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach have achieved sound performance for ...
Visual Studio Magazine

Anomaly Detection Using Principal Component Analysis (PCA)

A good way to see where this article is headed is to take a look at the screen shot of a demo program shown in Figure 1. The demo sets up a dummy dataset of six items: [ 5.1 3.5 1.4 0.2] [ 5.4 3.9 1.7 ...