Bernoulli Distribution

Protected: Regret Analysis for Stochastic Banded Problems

Regret analysis for stochastic banded problems utilized in digital transformation, artificial intelligence, and machine learning tasks (sum of equal sequences, gamma function, Thompson extraction, beta distribution, hem probability, Mills ratio, partial integration, posterior sample, conjugate prior distribution, Bernoulli distribution, cumulative distribution function, expected value, DMED measure, UCB measure, Chernoff-Hefding inequality, likelihood, upper bound, lower bound, UCB score, arms)

2023.01.13

アルゴリズム:Algorithms強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Measures for Stochastic Bandid Problems Stochastic Matching Method and Thompson Extraction

Stochastic bandit problem measures utilized in digital transformation, artificial intelligence, and machine learning tasks Stochastic matching methods and Thompson extraction worst-case riglet minimization, problem-dependent riglet minimization, worst-case riglet upper bounds, problem-dependent riglet, worst-case riglet, and MOSS measures, sample averages, correction terms, UCB liglet upper bounds, adversarial bandit problems, Thompson extraction, Bernoulli distribution, UCB measures, stochastic matching methods, stochastic bandit, Bayesian statistics, KL-UCCB measures, softmax measures, Chernoff-Heffding inequality

2022.12.23

アルゴリズム:Algorithmsオンライン学習バンディッド問題強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Measures for Stochastic Banded Problems Likelihood-based measures (UCB and MED measures)

Measures for Stochastic Banded Problems Likelihood-based UCB and MED measures (Indexed Maximum Empirical Divergence policy, KL-UCB measures, DMED measures, Riglet upper bound, Bernoulli distribution, Large Deviation Principle, Deterministic Minimum Empirical Divergence policy, Newton's method, KL divergence, Binsker's inequality, Heffding's inequality, Chernoff-Heffding inequality, Upper Confidence Bound)

2022.12.09

アルゴリズム:Algorithmsバンディッド問題幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Fundamentals of Stochastic Bandid Problems

Basics of stochastic bandid problems utilized in digital transformation, artificial intelligence, and machine learning tasks (large deviation principle and examples in Bernoulli distribution, Chernoff-Heffding inequality, Sanov's theorem, Heffding inequality, Kullback-Leibler divergence, probability mass function, hem probability, probability approximation by central limit theorem).

2022.11.11

バンディッド問題強化学習微分積分:Calculus機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Bayesian Learning and Conjugacy

Conjugacy of various probability functions (Gaussian, Bernoulli, Poisson, Dirichlet, and Gamma distributions) and prior distributions for Bayesian learning calculations in stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks

2022.10.13

アルゴリズム:Algorithmsベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Various probability distributions

Overview of various probabilistic models used as approximate models for probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks (Student's t distribution, Wishart distribution, Gaussian distribution, gamma distribution, inverse gamma distribution, Dirichlet distribution, beta distribution, categorical distribution, Poisson distribution, Bernoulli distribution)

2022.07.05

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra