28 citations · 91 across the 17 of their papers we have counts for
4 papers · 1 filter
Detecting Anomalies within Time Series using Local Neural Transformations
Tim Schneider, Chen Qiu, Marius Kloft +4
We develop a new method to detect anomalies within time series, which is essential in many application domains, reaching from self-driving cars, finance, and marketing to medical d…
Learning Gradual Argumentation Frameworks using Genetic Algorithms
Jonathan Spieler, Nico Potyka, Steffen Staab
Gradual argumentation frameworks represent arguments and their relationships in a weighted graph. Their graphical structure and intuitive semantics makes them a potentially interes…
LaHAR: Latent Human Activity Recognition using LDA
Zeyd Boukhers, Danniene Wete, Steffen Staab
Processing sequential multi-sensor data becomes important in many tasks due to the dramatic increase in the availability of sensors that can acquire sequential data over time. Huma…
MOFA: Modular Factorial Design for Hyperparameter Optimization
Bo Xiong, Yimin Huang, Hanrong Ye +2
This paper presents a novel and lightweight hyperparameter optimization (HPO) method, MOdular FActorial Design (MOFA). MOFA pursues several rounds of HPO, where each round alternat…