the optional stopping theorem says about martingales and stopping times

Kolmogorov complexity

Kolmogorov complexity is uncomputable

the minimax theorem says: in zero-sum games, there's a saddle point strategy

In zero-sum games, minimax theorem guarantees a saddle point strategy

Law of large numbers

Law of large numbers: X̄_ n → μ as n → ∞ with probability 1

Local martingale

E[X_{n+1}|X_1,...,X_n] = X_n

temperature T in softmax(x/T) controls entropy: T→0 is argmax, T→∞ is uniform

As T approaches 0, softmax concentrates probabilities; as T approaches ∞, probabilities become uniform

t-SNE preserves local structure

t-SNE preserves local structure by converting distances to probabilities and minimizing Kullback-Leibler divergence