オンライン学習 Protected: Reinforcement Learning with Function Approximation (3) – Function Approximation for Policy Functions
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最適化:Optimization
オンライン学習 オンライン学習 Protected: Reinforcement Learning with Function Approximation (2) – Function Approximation of Value Functions (For Online Learning)
Theory of function approximation online methods gradient TD learning, least-squares based least-squares TD learning (LSTD), GTD2)for reinforcement learning with a huge number of states used in digital transformation , artificial intelligence , and machine learning tasks, and regularization with LASSO.
強化学習 Protected: Reinforcement Learning with Function Approximation (1) – Function Approximation of Value Functions (Batch Learning Case)
Function approximation in the case of batch learning of value functions to deal with a huge number of states in reinforcement learning for digital transformation, artificial intelligence, and machine learning tasks.
IOT技術:IOT Technology Protected: Model-based reinforcement learning(Sparse sampling, UCT, Monte Carlo search tree)
Model-based reinforcement learning (sparse sampling, UCT, Monte Carlo search trees) used for digital transformation artificial intelligence , and machine learning tasks.
グラフ理論 Structural Learning
About Structural Learning
Learning the structure that data has is important for interpreting what the data is a...
微分積分:Calculus Machine Learning Professional Series “Continuous Optimization for Machine Learning” Reading Memo
Summary
Continuous optimization in machine learning is a method for solving optimization problems in which varia...
IOT技術:IOT Technology Protected: Model-free reinforcement learning (2) – Method iteration (Q-learning, SARSA, Actor-click method)
Value iteration methods Q-learning, SARSA, Actor-critic methods to model-free reinforcement learning for digital transformation , artificial intelligence and machine learning tasks.
オンライン学習 Protected: Trade-off between exploration and utilization -Regret and stochastic optimal measures, heuristics
Reinforcement learning with regrets, stochastic optimal measures, and heuristics
IOT技術:IOT Technology Time series data analysis
Overview of Time Series Data Learning
Time-series data is called data whose values change over time, suc...
オンライン学習 Protected: Planning Problems (2) Implementation of Dynamic Programming (Value Iterative Method and Measure Iterative Method)
Implementation of Dynamic Programming (Value Iteration and Policy Iteration) for Planning Problems as Reinforcement Learning for Digital Transformation , Artificial Intelligence and Machine Learning Tasks