2023-03

アルゴリズム:Algorithms

Protected: Explainable Artificial Intelligence (16) Model independent interpretation (SHAP (SHapley Additive exPlanations))

Model independent interpretation with SHAP as an explainable artificial intelligence used for digital transformation, artificial intelligence and machine learning tasks scikit-learn, xgboost, LightGBM, tree boosting, R, shapper, fastshap, TreeSHAP, KernelSHAP, partial dependence plot, permutation feature importance, feature importance, feature dependence, interactions, clustering, summary plots clustering, summary plots, atomic unit, LIME, decision tree, game theory, clustering, SHAP interaction values, ALE plot, image mapping, consistency, missing, local correctness, efficiency, symmetry, dummyness, additivity, SHapley Additive exPlanations, local surrogate models
アルゴリズム:Algorithms

Protected: Value Assessment and Policy and Weaknesses in Deep Reinforcement Learning

Value assessment and strategies and weaknesses in deep reinforcement learning used for digital transformation, artificial intelligence, and machine learning tasks poor sample efficiency, difficulty in validating methods as well, impact of implementation practices on performance, library initial values, poor reproducibility, over-training, local optimum, dexterity, TRPO, PPO, continuous value control, image control, policy-based, value-based
Clojure

Implementation using Clojure’s graphical tools seesaw and Quill

UI (graphics, libraries, Quill, tutorial, user interface, Java, Swing) with simple graphical tools using Clojure/seesaw utilized for digital transformation (DX), artificial intelligence (AI), machine learning (ML) tasks.
プログラミング言語:Programming Language

Differences between statically/dynamically typed languages in programming

Differences between statically/dynamically typed languages in programming used for digital transformation, artificial intelligence, and machine learning tasks Haskell, Scala, Java, type inference, JSON, automated unit testing, compilation, agile development, waterfall development, data structures, interfaces, method signatures, readability, Ruby, ease of writing, execution speed, acceleration, C, C++, Pyhton
推論技術:inference Technology

Overview and Implementation of the Satisfiability Determination Problem (SAT: Boolean SAtisfiability) of Propositional Logic

Overview and implementation of the satisfiability decision problem (SAT: Boolean SAtisfiability) for propositional logic, which is used in digital transformation, artificial intelligence, and machine learning tasks Clojure Rollingstones, Pyhton, PySAT, z3-solver, C++, 2-SAT, game AI, natural language processing acceleration, combinatorial optimization problem efficiency, hyperparameter optimization, computer security, automatic software specification verification, automatic chip design verification, zChaff, WalkSAT, GRASP, CryptoMiniSat, MapleSAT, Scavel, PicoSAT, MiniSAT, CaDiCaL, Lingeling, Glucose, P≠NP prediction, logic problems
ICT技術:ICT Technology

Artificial Intelligence Technology as a Case Study in DX

Specific Applications of Artificial Intelligence Technology for DX Applications Artificial intelligence...
Large-Scaleデータ

Parallel and Distributed Processing in Machine Learning

Parallel and Distributed Processing in Machine Learning The learning process of machine learning requires hi...
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
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