7 citations · 11 across the 5 of their papers we have counts for
5 papers
Rapid Augmentations for Time Series (RATS): A High-Performance Library for Time Series Augmentation
Wadie Skaf, Felix Kern, Aryamaan Basu Roy +3
Time series augmentation is critical for training robust deep learning models, particularly in domains where labelled data is scarce and expensive to obtain. However, existing augm…
Client Error Clustering Approaches in Content Delivery Networks (CDN)
Ermiyas Birihanu, Jiyan Mahmud, Péter Kiss +6
Content delivery networks (CDNs) are the backbone of the Internet and are key in delivering high quality video on demand (VoD), web content and file services to billions of users.…
Matrix Factorization for Cache Optimization in Content Delivery Networks (CDN)
Adolf Kamuzora, Wadie Skaf, Ermiyas Birihanu +6
Content delivery networks (CDNs) are key components of high throughput, low latency services on the internet. CDN cache servers have limited storage and bandwidth and implement sta…
Towards Automatic Forecasting: Evaluation of Time-Series Forecasting Models for Chickenpox Cases Estimation in Hungary
Wadie Skaf, Arzu Tosayeva, Dániel T. Várkonyi
Time-Series Forecasting is a powerful data modeling discipline that analyzes historical observations to predict future values of a time-series. It has been utilized in numerous app…
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series
Wadie Skaf, Tomáš Horváth
Anomalies in time-series provide insights of critical scenarios across a range of industries, from banking and aerospace to information technology, security, and medicine. However,…