2022-02

オンライン学習

Protected: Online Convex Optimization (2) Complementing FTL Strategies with Regularization

Complementing the FTL strategy by introducing regularization techniques (L2 norm) in online prediction for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Online Convex Optimization(1) FTL strategy and BTL supplement

Online Convex Optimization and FTL Strategies with Online Prediction for Digital Transformation , Artificial Intelligence , and Machine Learning Tasks with BTL Supplement
オンライン学習

Protected: New Developments in Reinforcement Learning (2) – Approaches Using Deep Learning

On seven methods for improving deep reinforcement learning used in digital transformation , artificial intelligence , and machine learning tasks (first generation DQN, dual Q learning (dual DQN method), prioritized experience replay, collision Q networks, distributed reinforcement learning (categorical DQN method) noise networks, n-step cutting returns) and alpha zero
life tips

Zen thought and history, Mahayana Buddhism, Taoist thought, Christianity

  Zen thought and history, Mahayana Buddhism, Taoist thought, Christianity Zen, derived from the Zen sect of Bud...
仏教:Buddhism

Dogen Zen master

Summary The book, "Dogen Zenji" by Izumi Kyoka Prize for Literature and Shinran Prize winner Tatematsu Wahei, is ...
web技術:web technology

ISWC2013 Papers

ISWC2013 Papers From ISWC2013, an international conference on Semantic Web technology, one of the artificial i...
オンライン学習

Protected: New Developments in Reinforcement Learning (1) – Reinforcement Learning with Risk Indicators

Different approaches (regular process TD learning, RDPS methods) and implementations (Monte Carlo, analytical methods) in risk-aware reinforcement learning methods for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Partially Observed Markov Decision Processes (2) Planning POMDPs

Reinforcement learning for digital transformation , artificial intelligence , and machine learning tasks; obtaining optimal strategies using partial observation Markov decision process planning methods.
オンライン学習

Protected: Partially Observed Markov Decision Processes (1) On POMDPs and Belief MDPs

Belief MDPs, more flexible reinforcement learning using partially observed Markov decision processes (POMDPs) for digital transformation , artificial intelligence , and machine learning tasks.
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