- Sungjin Im, Ravi Kumar 0001, Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii. Massively Parallel Computation: Algorithms and Applications. Foundations and Trends in Optimization, 5(4):340-417, 2023.
- David B. Brown, James E. Smith 0003. Information Relaxations and Duality in Stochastic Dynamic Programs: A Review and Tutorial. Foundations and Trends in Optimization, 5(3):246-339, 2022.
- Changliu Liu, Tomer Arnon, Christopher Lazarus, Christopher A. Strong, Clark W. Barrett, Mykel J. Kochenderfer. Algorithms for Verifying Deep Neural Networks. Foundations and Trends in Optimization, 4(3-4):244-404, 2021.
- Alexandre d'Aspremont, Damien Scieur, Adrien Taylor. Acceleration Methods. Foundations and Trends in Optimization, 5(1-2):1-245, 2021.
- Ruidi Chen, Ioannis Ch. Paschalidis. Distributionally Robust Learning. Foundations and Trends in Optimization, 4(1-2):1-243, 2020.
- Zhenan Fan, Halyun Jeong, Yifan Sun, Michael P. Friedlander. Atomic Decomposition via Polar Alignment: The Geometry of Structured Optimization. Foundations and Trends in Optimization, 3(4):280-366, 2020.
- Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar. Optimization Methods for Financial Index Tracking: From Theory to Practice. Foundations and Trends in Optimization, 3(3):171-279, 2018.
- Dmitriy Drusvyatskiy, Henry Wolkowicz. The Many Faces of Degeneracy in Conic Optimization. Foundations and Trends in Optimization, 3(2):77-170, 2017.
- Stephen P. Boyd, Enzo Busseti, Steve Diamond, Ronald N. Kahn, Kwangmoo Koh, Peter Nystrup, Jan Speth. Multi-Period Trading via Convex Optimization. Foundations and Trends in Optimization, 3(1):1-76, 2017.
- Alex Lemon, Anthony Man-Cho So, Yinyu Ye. Low-Rank Semidefinite Programming: Theory and Applications. Foundations and Trends in Optimization, 2(1-2):1-156, 2016.