hummingbird

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)
2023.03.24
アルゴリズム:Algorithmsグラフ理論スパースモデリングバンディッド問題幾何学:Geometry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
アルゴリズム:Algorithms

Protected: Evaluation of Rademacher Complexity and Prediction Discrimination Error in Multi-Valued Discrimination Using Statistical Mathematics Theory

Rademacher Complexity and Prediction Discriminant Error in Multivalued Discrimination by Statistical Mathematics Theory Used in Digital Transformation, Artificial Intelligence and Machine Learning Tasks Convex quadratic programming problems, mathematical programming, discriminant machines, prediction discriminant error, Bayesian error, multilevel support vector machines, representation theorem,. Rademacher complexity, multilevel marginals, regularization terms, empirical loss, reproducing nuclear Hilbert spaces, norm constraints, Lipschitz continuity, predictive Φp-multilevel marginals loss, empirical Φ-multilevel marginals loss, uniform bounds, discriminant functions, discriminant
2023.03.23
アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学: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
アルゴリズム:Algorithms

Protected: Two-Pair Extended Lagrangian and Two-Pair Alternating Direction Multiplier Methods as Optimization Methods for L1-Norm Regularization

Optimization methods for L1 norm regularization in sparse learning utilized in digital transformation, artificial intelligence, and machine learning tasks FISTA, SpaRSA, OWLQN, DL methods, L1 norm, tuning, algorithms, DADMM, IRS, and Lagrange multiplier, proximity point method, alternating direction multiplier method, gradient ascent method, extended Lagrange method, Gauss-Seidel method, simultaneous linear equations, constrained norm minimization problem, Cholesky decomposition, alternating direction multiplier method, dual extended Lagrangian method, relative dual gap, soft threshold function, Hessian matrix
2023.03.22
アルゴリズム:Algorithmsグラフ理論スパースモデリングスパースモデリング幾何学: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集合論:Set theory
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)
2023.03.21
アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学: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
アルゴリズム:Algorithms

Protected: Confidence Region Methods in Sequential Optimization in Machine Learning

Confidence region methods (dogleg method, norm constraint, model function optimization, approximate solution of subproblems, modified Newton method, search direction, globally optimal solution, Newton method, steepest descent method, confidence region radius, confidence region, descent direction, step width) in continuous optimization in machine learning used for digital transformation, artificial intelligence, machine learning tasks.
2023.03.20
アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学: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
ビジネス:Business

Writing papers/reports

Writing papers/reports There are many steps involved in writing a paper or report, i...
2023.03.19
ビジネス:Business課題解決:Problem solving論文作成
アルゴリズム:Algorithms

Recommendation Technology

  Recommendation Technology Overview Recommendation technology using machine learning can analyze a user's pas...
2023.03.19
アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学:Geometry微分積分:Calculus推薦技術最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
コンピューター

Overview of Semiconductor Manufacturing Technology and Application of AI Technology

Overview of semiconductor manufacturing technology and application of AI technology front-end process, wafer fabrication, cleaning process, deposition process, lithography process, etching process, impurity diffusion process, etc.; back-end process, dicing, mounting, bonding, molding, marking, bumping process, packaging, diffusion, ion implantation Annealing, wet etching, dry etching, immersion lithography system, EUV, AR excimer laser, Moore's law, 2nm, photosensitizer, photoengraving technology, stepper, thermal oxidation, CVD, sputter, Choklarsky method, ingot, Si wafer
2023.03.18
コンピューターテクノロジー:Technologyハードウェア
Uncategorized

Protected: Explainable Artificial Intelligence (15) model-independent interpretation (sharpley value)

Model-independent interpretation with Sharpe Ray values as explainable artificial intelligence used for digital transformation, artificial intelligence, and machine learning tasks breakDown, fastshap, R language, symmetry axioms, LIME, SHAP, sparse explanation, efficiency, symmetry, dummy, additivity principle, Sharpe Ray values, cooperative game theory
2023.03.17
Uncategorized
アルゴリズム:Algorithms

Protected: TRPO/PPO and DPG/DDPG, an improvement of the Policy Gradient method of reinforcement learning

TRPO/PPO and DPG/DDPG (Pendulum, Actor Critic, SequentialMemory, SequentialMemory, and SequentialMemory), which are improvements of Policy Gradient methods of reinforcement learning used for digital transformation, artificial intelligence, and machine learning tasks. Adam, keras-rl, TD error, Deep Deterministic Policy Gradient, Deterministic Policy Gradient, Advanced Actor Critic, A2C, A3C, Proximal Policy Optimization, Trust Region Policy Optimization, Python)
2023.03.16
アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
次のページ
タイトルとURLをコピーしました