ICT技術:ICT Technology Artificial Intelligence Technology as a Case Study in DX
Specific Applications of Artificial Intelligence Technology for DX Applications
Overview
Artificial in...
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ICT技術:ICT Technology Large-Scaleデータ Parallel and Distributed Processing in Machine Learning
Technical Topics of Parallel and Distributed Processing in Machine Learning
Overview
The learning process o...
IOT技術:IOT Technology The basic operation of the physical level of wireless communication
On the basic physical level operation of wireless communications utilized for digital transformation, artificial intelligence, and machine learning tasks (carrier frequency, channel, bandwidth, Bluetooth, carrier, 2.4 GHz, amplitude modulation, frequency modulation, SoC, horn antenna , dipole antennas, monopole antennas, microstrip antennas, Yagi-Uda antennas, Heinrich Hertz, Maxwell's equations, James Clerk Maxwell, wireless communications)
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: 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
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
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: 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.
ビジネス:Business Writing papers/reports
Writing papers/reports
Overview
There are many steps involved in writing a paper or...
アルゴリズム:Algorithms Recommendation Technology
Recommendation Technology
Overview
Recommendation technology using machine learning can analyze a user's pa...