algorithm

アルゴリズム:Algorithms

Protected: Optimal arm bandit and Bayesian optimal when the player’s candidate actions are huge or continuous (2)

Bayesian optimization for digital transformation, artificial intelligence, machine learning tasks and bandit when player behavior is massive/continuous Markov chain Monte Carlo, Monte Carlo integration, turn kernels, scale parameters, Gaussian kernels, covariance function parameter estimation, Simultaneous Optimistic Optimazation policy, SOO strategy, algorithms, GP-UCB policy, Thompson's law, expected value improvement strategy, GP-UCB policy
アルゴリズム:Algorithms

Protected: Thompson Sampling, linear bandit problem on a logistic regression model

Thompson sampling, linear bandit problem on logistic regression models utilized in digital transformation, artificial intelligence, and machine learning tasks (Thompson sampling, maximum likelihood estimation, Laplace approximation, algorithms, Newton's method, negative log posterior probability, gradient vector, Hesse matrix, Laplace approximation, Bayesian statistics, generalized linear models, Lin-UCB measures, riglet upper bound)
アルゴリズム:Algorithms

Protected: Linear Bandit, Contextual Bandit, Linear Bandit Problem with LinUCB Policies

Linear Bandit, Contextual Bandit, LineUCB policy for linear bandit problems (Riglet, algorithm, least squares quantification, LinUCB score, reward expectation, point estimate, knowledge) utilized in digital transformation, artificial intelligence, machine learning tasks utilization-oriented measures, search-oriented measures, Woodbury's formula, LinUCB measures, LinUCB policy, contextual bandit, website optimization, maximum sales expectation, bandit optimal budget allocation)
アルゴリズム:Algorithms

Protected: An example of machine learning by Bayesian inference: inference by Gibbs sampling of a Gaussian mixture model

Example of learning Bayesian inference utilized in digital transformation, artificial intelligence, and machine learning tasks: inference with Gibbs sampling of Gaussian mixture models (algorithms, observation models, Poisson mixture models, Wishart distribution, multidimensional Gaussian distribution, conditional distribution, and Gaussian Wishart distribution, latent variable, categorical distribution)
アルゴリズム:Algorithms

Protected: Optimization methods for L1-norm regularization for sparse learning models

Optimization methods for L1-norm regularization for sparse learning models for use in digital transformation, artificial intelligence, and machine learning tasks (proximity gradient method, forward-backward splitting, iterative- shrinkage threshholding (IST), accelerated proximity gradient method, algorithm, prox operator, regularization term, differentiable, squared error function, logistic loss function, iterative weighted shrinkage method, convex conjugate, Hessian matrix, maximum eigenvalue, second order differentiable, soft threshold function, L1 norm, L2 norm, ridge regularization term, η-trick)
アルゴリズム:Algorithms

Protected: Optimal arm identification and AB testing in the bandit problem_2

Optimal arm identification and AB testing in bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks sequential deletion policy, false positive rate, fixed confidence, fixed budget, LUCB policy, UCB policy, optimal arm, score-based method, LCB, algorithm, cumulative reward maximization, optimal arm identification policy, ε-optimal arm identification
アルゴリズム:Algorithms

Protected: Example of Machine Learning with Bayesian Inference: Variational Inference for Poisson Mixture Models

Examples of machine learning with Bayesian inference utilized for digital transformation, artificial intelligence, and machine learning tasks: variational inference for Poisson mixed models (Gibbs sampling, variational inference, algorithm, ELBO, computation, variational inference algorithm, latent variable parameters, posterior distribution, Dirichlet distribution, gamma distribution)
アルゴリズム:Algorithms

Theory and algorithms of various reinforcement learning techniques and their implementation in python

Theory and algorithms of various reinforcement learning techniques used for digital transformation, artificial intelligence, and machine learning tasks and their implementation in python reinforcement learning,online learning,online prediction,deep learning,python,algorithm,theory,implementation
Clojure

Protected: Network analysis in GraphX Pregel using Clojure

Network analysis in GraphX Pregel using Clojure for digital transformation, artificial intelligence, and machine learning tasks (label propagation, twitter data, community analysis, graph structure analysis, community size, community detection, algorithms, maximum connected components, triangle counting, glittering, Google, Koenigsberg bridge, Euler path)
アルゴリズム:Algorithms

Protected: An example of machine learning by Bayesian inference: inference by Gibbs sampling of a Poisson mixture model

Examples of machine learning with Bayesian inference utilized for digital transformation, artificial intelligence, and machine learning tasks: inference by Gibbs sampling of Poisson mixed models (algorithm, sampling of unobserved variables, Dirichlet distribution, gamma distribution, conditional distribution, categorical distribution, posterior distribution, simultaneous distribution, superparameter, knowledge model, latent variable) categorical distribution, posterior distribution, simultaneous distribution, hyperparameters, knowledge models, data generating processes, latent variables)
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