artificial intelligence

アルゴリズム:Algorithms

Protected: Research Trends in Deep Reinforcement Learning: Meta-Learning and Transfer Learning, Intrinsic Motivation and Curriculum Learning

Research trends in deep reinforcement learning for digital transformation, artificial intelligence, and machine learning tasks: meta-learning and transfer learning, intrinsic motivation and curriculum learning automatic curriculum generation, automatic task decomposition, task difficulty adjustment, intrinsic reward, robot domain transformation, robot domain transformation, simulator to simulator transfer learning, BERT, Metric/Representation Base, Memory/Knowledge Base, active learning, meta-learning, and robot domain transformation) Robot domain transformation, transfer learning from simulators, BERT, Model-Agnostic Meta-Learning, Active Learning, Metric/Representation Base, Memory/Knowledge Base, Weigh Base, and Learning to Optimize
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: Sparse Machine Learning with Overlapping Sparse Regularization

Sparse machine learning with overlapping sparse regularization for digital transformation, artificial intelligence, and machine learning tasks main problem, dual problem, relative dual gap, dual norm, Moreau's theorem, extended Lagrangian, alternating multiplier method, stopping conditions, groups with overlapping L1 norm, extended Lagrangian, prox operator, Lagrangian multiplier vector, linear constraints, alternating direction multiplier method, constrained minimization problem, multiple linear ranks of tensors, convex relaxation, overlapping trace norm, substitution matrix, regularization method, auxiliary variables, elastic net regularization, penalty terms, Tucker decomposition Higher-order singular value decomposition, factor matrix decomposition, singular value decomposition, wavelet transform, total variation, noise division, compressed sensing, anisotropic total variation, tensor decomposition, elastic net
アルゴリズム:Algorithms

Protected: Optimization for the main problem in machine learning

Optimization for main problems in machine learning used in digital transformation, artificial intelligence, and machine learning tasks (barrier function method, penalty function method, globally optimal solution, eigenvalues of Hesse matrix, feasible region, unconstrained optimization problem, linear search, Lagrange multipliers for optimality conditions, integration points, effective constraint method)
アルゴリズム:Algorithms

Protected: Applied Bayesian inference in non-negative matrix factorization: model construction and inference

Non-negative matrix factorization as a construction and inference of applied Bayesian inference models used in digital transformation, artificial intelligence, and machine learning tasks Poisson distribution, latent variable, gamma distribution, approximate posterior distribution, variational inference, spectogram of organ performance data, missing value interpolation, restoration of high frequency components, super-resolution, graphical models, hyperparameters, modeling, auxiliary variables, linear dimensionality reduction, recommendation algorithms, speech data, Fast Fourier Transform, natural language processing
Uncategorized

Protected: Explainable Machine Learning (18)Adversarial Examples

Explainable Machine Learning with Adversarial Sample Approach utilized for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Cyber Security, Surrogate Models, Neural Networks, Black Box Attack, Expectation Over Transformation algorithm, EOT, InceptionV3, TensorFlow, Fast gradient method, VGG16 classifier, ImageNet, adversarial patch, 1-pixel attack, L-BFGS method, Fast gradient sign method
アルゴリズム:Algorithms

Protected: Implementation of two approaches to improve environmental awareness, a weak point of deep reinforcement learning.

Implementation of two approaches to improve environment awareness, a weakness of deep reinforcement learning used in digital transformation, artificial intelligence, and machine learning tasks (inverse predictive, constrained, representation learning, imitation learning, reconstruction, predictive, WorldModels, transition function, reward function Weaknesses of representation learning, VAE, Vision Model, RNN, Memory RNN, Monte Carlo methods, TD Search, Monte Carlo Tree Search, Model-based learning, Dyna, Deep Reinforcement Learning)
Clojure

Overview of web crawling technologies and implementation in Python/Clojure

Overview of web crawling technologies used for digital transformation, artificial intelligence and machine learning tasks and their implementation in Python/Clojure jsoup, clj-http, enlive, clojure.data.json, HTML, CSS jsoup, HTML, CSS, XPATH, JSON, BeautifulSoup, Scrapy, data extraction, natural language processing, databases, search, SNS analysis
ICT技術:ICT Technology

Overview of Kubernetes, environment setup, and reference books

Overview and configuration of Kubernetes used for digital transformation, artificial intelligence and machine learning tasks, reference books (Microservices, Spinnaker, Blue, Containers, Cloud Natives, Skaffold, Clair, Security, BuildKit, Kaniko, Operator, Helm, Chart, Sock Shop, YAML, Prometheus, Grafana, Pod, Minikube)
アルゴリズム:Algorithms

Protected: Optimal arm bandit and Bayes optimal when the player’s candidate actions are large or continuous(1)

Optimal arm bandit and Bayes optimal linear curl, linear bandit, covariance function, Mattern kernel, Gaussian kernel, positive definite kernel function, block matrix, inverse matrix formulation, prior simultaneous probability density, Gaussian process, Lipschitz continuous, Euclidean norm, simple riglet, black box optimization, optimal arm identification, regret, cross checking, leave-one-out cross checking, continuous arm bandit
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