9 Result(s)
within
Computer Science
Artificial Intelligence
Data Structures and Information Theory
Information Storage and Retrieval
**ya Sato
Chapter
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Chapter and Conference Paper
Variance-Penalized Reinforcement Learning for Risk-Averse Asset Allocation
The tasks of optimizing asset allocation considering transaction costs can be formulated into the framework of Markov Decision Processes(MDPs) and reinforcement learning. In this paper, a risk-averse reinforce...
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A Flexible Modeling of Global Plasma Profile Deduced from Wave Data
As the plasma profile around the earth varies with local time, season and solar activity, it is important to have a means to determine it in a fine time resolution. In this paper we propose a method to determi...
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Chapter
EM Learning for Symbolic-Statistical Models in Statistical Abduction
We first review a logical-statistical framework called statistical abduction and identify its three computational tasks, one of which is the learning of parameters from observations by ML (maximum likelihood) est...
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Chapter
Discovery of Definition Patterns by Compressing Dictionary Sentences
This paper proposes an automatic method to discover definition patterns from an ordinary dictionary. There are frequent patterns to describe words and concepts in a ordinary dictionary. Each definition pattern...
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Chapter
Computational Analysis of Plasma Waves and Particles in the Auroral Region Observed by Scientific Satellite
In this paper we introduce new computational techniques for extracting the attributes and/or characteristics of the plasma waves and particles from the enormous scientific database. These techniques enable us ...
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Chapter and Conference Paper
A Hierarchical Model to Support Kansei Mining Process
Image retrieval by subjective content has been recently addressed by the Kansei engineering community in Japan. Such information retrieval systems aim to include subjective aspects of the users in the querying...
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Chapter
Refutable/Inductive Learning from Neighbor Examples and Its Application to Decision Trees over Patterns
The paper develops the theory of refutable/inductive learning as a foundation of discovery science from examples. We consider refutable/inductive language learning from positive examples, some of which may be ...
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Theory of Judgments and Derivations
We propose a computational and logical framework NF (Natural Framework) which is suitable for presenting mathematics formally. Our framework is an extendable framework since it is open-ended both computationally ...
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Chapter and Conference Paper
Semi-structure Mining Method for Text Mining with a Chunk-Based Dependency Structure
In text mining, when we need more precise information than word frequencies such as the relationships among words, it is necessary to extract frequent patterns of words with a dependency structure in a sentenc...
