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Machine Learning Theory Lab
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A lab that explores machine learning and online decision-making from a theoretical perspective.
AboutAbout the lab
Exploring how machine learning works, from theory.
The Machine Learning Theory Lab is a lab where Professor Eiji Takimoto and Professor Kohei Hatano study online decision-making, computational learning theory, machine learning, and related areas.
Based on the principles of the theory of computation, Prof. Takimoto conducts broad research centered on online decision-making, learning theory, and computational complexity theory.
Prof. Hatano works on computer science, especially machine learning.
The lab belongs to the Intelligence Science Group in the Department of Information Science and Technology.
Key terms
- Computational learning theory
- A field that uses mathematical theory to investigate how computers learn from examples
- Online decision-making
- The problem of making predictions or choices on the spot, depending on the situation
- Boosting
- A machine learning technique that combines predictions of modest accuracy to produce better predictions
ResearchResearch themes
Based on the principles of the theory of computation, Prof. Takimoto focuses on online decision-making, learning theory, and computational complexity theory. Prof. Hatano works on the theoretical analysis of machine learning and the design of algorithms.
*Illustrative imageOnline Decision-Making and Prediction
Prof. Takimoto studies online decision-making with the keywords online prediction, online algorithms, competitive analysis, and game theory. Prof. Hatano works on the design and analysis of online prediction algorithms.
*Illustrative imageComputational Learning Theory
Prof. Takimoto studies computational learning theory with the keywords PAC learning, learning from queries, online learning, and boosting. Computational learning theory is also listed among Prof. Hatano's research themes.
*Illustrative imageComputational Complexity Theory
Prof. Takimoto studies computational complexity theory with the keyword Boolean circuits.
*Illustrative imageTheoretical Analysis and Design of Machine Learning
Prof. Hatano works on the theoretical analysis of machine learning and the design of algorithms. The listed keywords are computational learning theory, data mining, boosting, and optimization.
MembersFaculty
- ProfessorEiji Takimoto
- ProfessorKohei Hatano
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Decision Tree Anatomy” Lapollard / CC BY-SA 4.0 (cropped)
- Online Decision-Making and Prediction: “DecisionCalcs” IPWAI / CC BY-SA 3.0 (cropped)
- Computational Learning Theory: “Pac-err” Tom M.Mitchell / CC BY-SA 4.0 (cropped)
- Computational Complexity Theory: “Puzzle offering knight” BeeBringer / CC0 (cropped)
- Theoretical Analysis and Design of Machine Learning: “CSIRO ScienceImage 11313 The CSIRO GPU cluster at the data centre” division, CSIRO / CC BY 3.0 (cropped)
- Related lab (文化知能科学研究室): “Jacques-Louis David - Oath of the Horatii - Google Art Project” Anne-Louis Girodet / After Jacques-Louis David / Public domain (cropped)
- Related lab (マルチエージェント研究室): “Agreement-between-TCO-and-SACO” Unknown photographer / Public domain (cropped)
- Related lab (統計的学習研究室): “AI relation to Generative Models subset, venn diagram” The Original Benny C / CC BY-SA 4.0 (cropped)
- Related lab (人間情報科学研究室): “NASA Medical Monitoring 4” NASA / Public domain (cropped)
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