Ref.No: | 61515900 |
Start date: | 17.03.2023 |
End date: | 16.10.2025 |
Approval date: | 10.03.2023 |
Department: | ELECTRICAL & COMPUTER ENGINEERING |
Sector: | COMPUTER SCIENCE |
Financier: | 4Η ΠΡΟΚΗΡΥΞΗ ΕΛΙΔΕΚ ΓΙΑ Υ.Δ., ELIDEK |
Budget: | 27.900,00 € |
Public key: | ΨΨΡΨ46ΨΖΣ4-ΖΦΞ |
Scientific Responsible: | Assoc. Prof. DIMITRIOS FOTAKIS |
Email: | fotakis@cs.ntua.gr |
Description: | CURRENT MACHINE LEARNING METHODS DEMAND STRICTLY DEFINED RELATIONS BETWEEN DATA WITHIN A DATASET. ALTHOUGH MOST OF THESE RELATIONS ARE MORE COMPLEX AND COULD BE BETTER REPRESENTED THROUGH GRAPHS. THE ABOVE OBSERVATION HAS DRIVEN A SIGNIFICANT PART OF RES |