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Synthesis lectures on artificial intelligence and machine learning

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Synthesis lectures on artificial intelligence and machine learning

Material type
図書
Author
-
Publisher
Morgan & Claypool
Publication date
2007
Material Format
Paper
Capacity, size, etc.
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NDC
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Paper

Material Type
図書
Publication, Distribution, etc.
Publication Date (W3CDTF)
2007
Place of Publication (Country Code)
us
Target Audience
一般
Related Material
Introduction to Intelligent systems in traffic and transportation
A concise introduction to models and methods for automated planning
Graph-based semi-supervised learning
Intelligent autonomous robotics : a robot soccer case study
Lifelong machine learning
Active learning
Judgment aggregation : a primer
Visual object recognition
Markov logic : an interface layer for artificial intelligence
Adversarial machine learning
An introduction to constraint-based temporal reasoning
Planning with Markov Decision Processes: an AI perspective
Essentials of game theory : a concise, multidisciplinary introduction
Transfer learning for multiagent reinforcement learning systems
Transfer learning for multiagent reinforcement learning systems
Introduction to graph neural networks
Applying reinforcement learning on real-world data with practical examples in Python
Markov logic : an interface layer for artificial intelligence
Toward robots that reason : logic, probability & causal laws
Introduction to semi-supervised learning
Human computation
Computational aspects of cooperative game theory
Essential principles for autonomous robotics
Algorithms for reinforcement learning
Game theory for data science : eliciting truthful information
Graph representation learning
Federated learning
Introduction to graph neural networks
Metric learning
Introduction to graph neural networks
Graph representation learning
Statistical relational artificial intelligence : logic, probability, and computation
Lifelong machine learning
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