4 papers
Learning K-U-Net with constant complexity: An Application to time series forecasting
Jiang You, Arben Cela, René Natowicz +2
Training deep models for time series forecasting is a critical task with an inherent challenge of time complexity. While current methods generally ensure linear time complexity, ou…
Anomaly Prediction: A Novel Approach with Explicit Delay and Horizon
Jiang You, Arben Cela, René Natowicz +2
Anomaly detection in time series data is a critical challenge across various domains. Traditional methods typically focus on identifying anomalies in immediate subsequent steps, of…
Robust Time Series Forecasting with Non-Heavy-Tailed Gaussian Loss-Weighted Sampler
Jiang You, Arben Cela, René Natowicz +2
Forecasting multivariate time series is a computationally intensive task challenged by extreme or redundant samples. Recent resampling methods aim to increase training efficiency b…
A Nonlinear African Vulture Optimization Algorithm Combining Henon Chaotic Mapping Theory and Reverse Learning Competition Strategy
Baiyi Wang, Zipeng Zhang, Patrick Siarry +5
In order to alleviate the main shortcomings of the AVOA, a nonlinear African vulture optimization algorithm combining Henon chaotic mapping theory and reverse learning competition…