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Exceeding Computational Complexity Trial-and-Error Dynamic Action and Intelligence
Computational complexity is a core theory of computer science, which dictates the degree of difficulty of computation.
Sampling and Complexity of Partition Function
In this article, we discuss the set up of the partition function, properties of the partition function, and the tools to be used.
Computational Complexity
Sampling and Learning for Boolean Function
In this article, we continue our study on universal learning machine by introducing new tools.
Algebraic Expression of Subjective Spatial and Temporal Patterns
Universal learning machine is a theory trying to study machine learning from mathematical point of view.
What Really is Deep Learning Doing?
From this particular angle, we can see deep learning much better and answer with confidence: What deep learning is really doing?
Descriptions of Objectives and Processes of Mechanical Learning
We prove that for any objective pattern we can find a proper subjective pattern based upon least base patterns to express the objective pattern well.
Discussion on Mechanical Learning and Learning Machine
Mechanical learning is a computing system that is based on a set of simple and fixed rules, and can learn from incoming data.
