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How Intelligent Can Computers Be?
Theory, Algorithm, and Application of Machine Learning
With the dramatic performance improvement of information and communication technology,
intelligent information processing that can be done only by humans
is becoming possible also by computers.
Under the theme of "how intelligent can computers be?",
Sugiyama-Sato Laboratory is working on various research topics
related to intelligent data analysis, called machine learning,
in the field of artificial intelligence.
- Construction of Learning Theory
Generalization is the ability to be able to cope with unknown situations,
and is indispensable for computers to behave intelligently.
We are theoretically investigating the mechanism of acquiring the generalization capability
based mainly on probability and statistics.
- Development of Learning Algorithms
Machine learning involves various subjects such as
supervised learning (learning from input-output paired data),
unsupervised learning (learning from input-only data),
and reinforcement learning (learning through interaction with an environment).
We are developing practical and theoretically motivated machine learning algorithms.
- Application of Machine Learning Technologies to Real-World
Growth and spread of the Internet and sensor technologies
allow us to collect a huge amount of data in engineering and fundamental sciences
such as documents, audio, images, movies, e-commerce, electric power, medicine, and biology.
We are collaborating with industry partners and applying
state-of-the-art machine learning technologies to solving real-world challenging problems.