アルゴリズム:Algorithms Simulation, Data Science and Artificial Intelligence
Topics on simulation and data science and artificial intelligence used for digital transformation , artificial intelligence and machine learning tasks
機械学習:Machine Learning
アルゴリズム:Algorithms IOT技術:IOT Technology Protected: Differences between hidden Markov models and state-space models and parameter estimation for state-space models
Differences between state-space models, Bayesian models, and hidden Markov models used in digital transformation, artificial intelligence, and machine learning tasks, and parameter estimation for state-space models
微分積分:Calculus Protected: Regression Analysis with Support Vector Machines (1)Approach to linear regression problems
Regression problems with linear functions using dual problems with Lagrangian functions with support vector machines utilized in digital transformation, artificial intelligence, and machine learning tasks
IOT技術:IOT Technology Protected: Time series data analysis (2) Filtering Sequential estimation of state and seasonal adjustment model
Prediction of time series using state-space models of time series data utilized in digital transformation, artificial intelligence, and machine learning; interpolation, parameter estimation, and analysis of store sales using component decomposition and standard seasonal adjustment models.
Symbolic Logic Uncertainty Reasoning for the Semantic Web 1
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...
Stream Data Processing Protected: Time Series Data Analysis (1) – State Space Model
Overview of various state-space models linear and Gaussian state-space models, AR models, autoregressive and moving average ARMA models, component decomposition models, and time-varying coefficient models) for time series data analysis used in digital transformation, artificial intelligence, and machine learning tasks
アルゴリズム:Algorithms Protected: Structural Regularization Learning with Submodular Optimization (3)Formulation of the structural regularization problem with submodular optimization
Application of submodular function optimization, an optimization method for discrete information, to structural regularization problems and formulations using submodular optimization (linear approximation and steepest effect methods, accelerated proximity gradient method, FISTA, parametric submodular minimization, and splitting algorithms)
アルゴリズム:Algorithms Protected: Structural regularization learning using submodular optimization (2) Structural sparsity obtained from submodular functions
Structural regularization learning (coupled Lasso and Lovász extensions) by structural sparsity obtained from submodular functions in submodular optimization, an optimization method for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.
Symbolic Logic Knowledge Graphs and Big Data Processing
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...
Symbolic Logic Reasoning Web 2007 Papers
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...