2023-05

python

Protected: Overcoming Weaknesses in Deep Reinforcement Learning Dealing with Poor Reproducibility: Evolutionary Strategies

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On the Road to Kanda

Summary Travel is an act for human beings to visit new places and experience different cultures and histories. Th...
仏教:Buddhism

About Buddhism, Scripture and Mahayana Buddhist Sects

  Buddhism Overview Buddhism, one of the world's three major religions (Christianity, Islam, and Buddhism), was fo...
python

Overview of the Bandit Problem and Examples of Application and Implementation

  Overview of the Bandit Problem The Bandit problem is a type of reinforcement learning in which a decision-ma...
アルゴリズム:Algorithms

Protected: Application of Bandit Method (3) Recommendation System

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アルゴリズム:Algorithms

Protected: Application of the Bandit Method (2) Internet Advertising

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アルゴリズム:Algorithms

Protected: Applications of the Bandit Method (1) Monte Carlo Tree Search

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python

Overview of sparse modeling and its application and implementation

Sparse Modeling Overview Sparse modeling is a technique that uses sparsity (sparse properties) in the ...
アルゴリズム:Algorithms

Protected: Extension of the Bandit Problem Partial Observation Problem

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アルゴリズム:Algorithms

Protected: Extension of the Bandit Problem – Time-Varying Bandit Problem and Comparative Bandit

Time-varying bandit problems and comparative bandits as extensions of bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks RMED measures, Condorcet winner, empirical divergence, large deviation principle, Borda winner, Coplan Winner, Thompson Extraction, Weak Riglet, Total Order Assumption, Sleeping Bandit, Ruined Bandit, Non-Dormant Bandit, Discounted UCB Measures, UCB Measures, Hostile Bandit, Exp3 Measures, LinUCB, Contextual Bandit
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