most citedRLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning

23 citations · 23 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 23 cited

RLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning

Tong Wu, Jorge Ortiz

We introduce a new semi-supervised, time series anomaly detection algorithm that uses deep reinforcement learning (DRL) and active learning to efficiently learn and adapt to anomal…

cs.LG2019

SECRET: Semantically Enhanced Classification of Real-world Tasks

Ayten Ozge Akmandor, Jorge Ortiz, Irene Manotas +2

Supervised machine learning (ML) algorithms are aimed at maximizing classification performance under available energy and storage constraints. They try to map the training data to…