Algorithmic Game Theory, Data Science, courses, conferences, journals, and books
Alon, N., & Spencer, J. H. (2016). The probabilistic method (Fourth edition. ed.). Wiley.
Echenique, F., N. Immorlica and V. V. Vazirani (2023). Online and matching-based market design. Cambridge, Cambridge University Press.
Blum, A., J. E. Hopcroft and R. Kannan (2020). Foundations of data science. New York, NY, Cambridge University Press.
Nisan, N. (2007). Algorithmic game theory. Cambridge University Press.
Vazirani, V. V. (2001). Approximation algorithms. Berlin ; New York, Springer.
Lovász, L. s. and M. D. Plummer (1986). Matching theory. Amsterdam ; New York New York, N.Y., North-Holland.
TTIC 31260 - Algorithmic Game Theory (Spring 2024)
TTIC 31150/CMSC 31150 - Mathematical Toolkit (Spring 2023)
COURSE: CS 15-892 Foundations of Electronic Marketplaces
Artificial Intelligence: Representation and Problem Solving
ACM Conference - Economics and Computation