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Explore a comprehensive seminar lecture from the Kolmogorov Seminar series that delves into the classical Vapnik-Chervonenkis theorem, examining why a small VC-dimension of hypotheses space leads to minimal error rates when comparing training and test samples. Learn from this in-depth 2.5-hour discussion that continues the legacy of the computational and descriptional complexity seminars established by Kolmogorov in 1979.
