Here are a few things you should know about complex systems, result of a worldwide collaborative effort from leading experts, practitioners and students in the field.
This page provides quick links to lecture notes that I have written for various classes: CS254: A graduate class on computational complexity (Stanford) [Spring 2010 Class Home Page] [Notes for Lectures 1-8] CS278: A graduate class on computational complexity (Berkeley) [Spring 2001 Class Home Page] [Fall 2002 Class Home Page] [2001 Lecture Notes in book…
S. Salimzadeh, G. He, and U. Gadiraju. Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, page 215-227. ACM, (June 2023)
X. Hu, W. Liu, J. Bian, and J. Pei. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, page 1521--1531. (2020)
M. Brennan, and G. Bresler. (2020)cite arxiv:2005.08099Comment: 175 pages; subsumes preliminary draft arXiv:1908.06130; accepted for presentation at the Conference on Learning Theory (COLT) 2020.
Y. Zhang, M. Wainwright, and M. Jordan. Proceedings of The 27th Conference on Learning Theory, volume 35 of Proceedings of Machine Learning Research, page 921--948. Barcelona, Spain, PMLR, (13--15 Jun 2014)
A. Achille, and S. Soatto. (2017)cite arxiv:1706.01350Comment: Deep learning, neural network, representation, flat minima, information bottleneck, overfitting, generalization, sufficiency, minimality, sensitivity, information complexity, stochastic gradient descent, regularization, total correlation, PAC-Bayes.