3 papers
cs.SE2025
Prompt2DAG: A Modular Methodology for LLM-Based Data Enrichment Pipeline Generation
Abubakari Alidu, Michele Ciavotta, Flavio DePaoli
Developing reliable data enrichment pipelines demands significant engineering expertise. We present Prompt2DAG, a methodology that transforms natural language descriptions into exe…
cs.LG2023
Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs
Stefano Fiorini, Stefano Coniglio, Michele Ciavotta +1
We introduce QuaterGCN, a spectral Graph Convolutional Network (GCN) with quaternion-valued weights at whose core lies the Quaternionic Laplacian, a quaternion-valued Laplacian mat…
cs.DC2017
A Game-Theoretic Approach for Runtime Capacity Allocation in MapReduce
Eugenio Gianniti, Danilo Ardagna, Michele Ciavotta +1
Nowadays many companies have available large amounts of raw, unstructured data. Among Big Data enabling technologies, a central place is held by the MapReduce framework and, in par…