Kernels, Data & Physics
Francesco Cagnetta Deborah Oliveira Mahalakshmi Sabanayagam Nikolaos Tsilivis Julia Kempe
Lecture notes from the course given by Professor Julia Kempe at the summer
school "Statistical physics of Machine Learning" in Les Houches. The notes
discuss the so-called NTK approach to problems in machine learning, which
consists of gaining an understanding of generally unsolvable problems by
finding a tractable kernel formulation. The notes are mainly focused on
practical applications such as data distillation and adversarial robustness,
examples of inductive bias are also discussed.