Spatial Economics & Machine Learning Theory: Intensive Seminar (2018)

From June to July this year, we held an intensive seminar to learn basic theories of spatial economics and machine learning. Here are the materials used in the seminar.

Spatial Economics Seminar

Based on: “The Spatial Economy: Cities, Regions, and International Trade” (Masahisa Fujita, Paul Krugman, Anthony J. Venables [author], Hiroyuki Koide [translator])

Chp. 1-3: Introduction, Urban Economics and Regional Science  ●Chp.1-3.pdf

Chp. 4-5: The Dixit-Stiglitz Model of Monopolistic Competition and Its Spatial Implications, Core and Periphery  ●Chp.4-5.pdf

Chp. 6-8: Many Regions and Continuous Space, Agricultural Transport Costs, Spatial Models of Urban Systems ●Chp.6-8.pdf

Chp. 9-10: The Monocentric Economy, The Emergence of New Cities ●Chp.9-10.pdf

Chp. 11-13: Evolution of a Hierarchical Urban System, An Empirical Digression, Ports, Transportation Hubs, and City Location ●Chp.11-13.pdf

Machine Learning Seminar

Deep Learning

Based on: “An Introduction to Deep Learning” (Masato Taki), “Deep Learning” (Takayuki Okatani) Deep Learning.pdf

Submodular function

Based on: “Machine learning with submodular functions” (Yoshinobu Kawahara, Kiyohito Nagano)

Submodular functions.pdf


Based on:”Relational Data Learning” (Katsuhiko Ishiguro, Kohei Hayashi)



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