7 papers
ChronoVAE-HOPE: Beyond Attention -- A Next-Generation VAE Foundation Model for Specialized Time Series Classification
José Alberto Rodríguez, Luis Balderas, Miguel Lastra +2
Time Series Foundation Models (TSFMs) have become a new component of the state-of-the-art in general time series forecasting. However, adapting them to specialized classification t…
KairosHope: A Next-Generation Time-Series Foundation Model for Specialized Classification via Dual-Memory Architecture
Luis Balderas, José Alberto Rodríguez, Miguel Lastra +2
Time Series Foundation Models (TSFMs) have demonstrated notable success in general-purpose forecasting tasks; however, their adaptation to specialized classification problems remai…
MoEITS: A Green AI approach for simplifying MoE-LLMs
Luis Balderas, Miguel Lastra, José M. Benítez
Large language models are transforming all areas of academia and industry, attracting the attention of researchers, professionals, and the general public. In the trek for more powe…
Sports center customer segmentation: a case study
Juan Soto, Ramón Carmenaty, Miguel Lastra +2
Customer segmentation is a fundamental process to develop effective marketing strategies, personalize customer experience and boost their retention and loyalty. This problem has be…
Optimizing Convolutional Neural Network Architecture
Luis Balderas, Miguel Lastra, José M. Benítez
Convolutional Neural Networks (CNN) are widely used to face challenging tasks like speech recognition, natural language processing or computer vision. As CNN architectures get larg…
Can persistent homology whiten Transformer-based black-box models? A case study on BERT compression
Luis Balderas, Miguel Lastra, José M. Benítez
Large Language Models (LLMs) like BERT have gained significant prominence due to their remarkable performance in various natural language processing tasks. However, they come with…