COMPUTATIONAL LEARNING THEORY



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
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