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# 統計と最適化

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Lectures on statistics and optimization as the foundations of machine learning.

コース名

0510009
FSC-IS2009L1

A1 A2

2

NO

- 確率変数と確率分布，確率分布の性質を表す指標/Random variables, probability distributions, and indices representing properties of probability distributions - 同時確率，条件付き確率/Joint probability, conditional probability - 離散型確率分布，連続型確率分布/Discrete probability distributions, continuous probability distributions - 任意の確率分布に従う標本の生成/Sampling from arbitrary probability distributions - 確率不等式/Probabilistic inequalities - 大数の法則と中心極限定理/Law of large numbers and central limit theorem - 重複対数の法則，仮説検定/Law of the iterated logarithm, hypothesis testing - 行列，微分積分，凸集合，凸関数/Matrices, differential and integral calculus, convex sets, convex functions - 制約なし最適化/Unconstrained optimization - 等式制約付き最適化/Equality constrained optimization - 不等式制約付き最適化/Inequality constrained optimization - 確率的最適化/Stochastic optimization - 自動微分/Automatic differentiation - 共役勾配法/Conjugate gradient method

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