GitHub

Prometheus Time Series Anomaly Detection with LSTM Autoencoder

This project implements a system for detecting anomalies in time series data collected from Prometheus. It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn ...
IEEE

A Weighted Smooth Q-Learning Algorithm

Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...
IEEE

Deep Q-Learning-Based Handover for Spectral Coexistence Between Feeder and User Links in LEO Satellite Networks

Abstract: Deploying feeder links (i.e., between satellites and ground stations) at Ka-band is becoming a popular option among satellite operators thanks to its consolidated technology maturity level.