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