アルゴリズム:Algorithms An overview of twitter’s recommendation algorithm
Overviews
Twitter Inc. has released a Twitter recommendation system that is getting a lot of attention.
Bel...
グラフ理論
アルゴリズム:Algorithms python Overview of automatic statement generation using Huggingface
Huggingface
Huggingface is an open source platform and library for machine learning and natural language pro...
アルゴリズム:Algorithms Example implementation for general time series analysis using R or Python
Overview of time series data analysis
Time-series data is called data whose values change over time, suc...
アルゴリズム:Algorithms Overview of LightGBM and its implementation in various languages
LightGBM Overview
LightGBM is a Gradient Boosting Machine (GBM) framework developed by Microsoft, which i...
アルゴリズム:Algorithms Time series analysis using Prophet
Prophet Overview
Prophet is a time-series forecasting tool developed by Facebook that will be able to...
アルゴリズム:Algorithms Protected: Hidden Markov model building and fully decomposed variational inference in Bayesian inference
Hidden Markov model building and fully decomposed variational inference (approximate posterior distribution, categorical distribution, Dirichlet distribution, expectation calculation, transition probability matrix, Poisson mixture model, variational inference) in Bayesian inference for digital transformation, artificial intelligence, machine learning tasks.
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)