I work in the field of nonlinear optimization, with a focus on derivative free optimization (DFO).
- Berahas, A. S., Cao, L., & Scheinberg, K. Analysis of a Trust Region Method with Errors (in preparation)
- Cao, L., Menickelly, M., & Wild, S.M. A Model-based Approach to Derivetive-free Multiobjective Optimization (in preparation)
- Wang, Fenlan, and Liyuan Cao. A New Algorithm for Quadratic Integer Programming Problems with Cardinality Constraint. Japan Journal of Industrial and Applied Mathematics (2020): 1-12.
- Berahas, A. S., Cao, L., Choromanski, K., & Scheinberg, K. (2019). A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. Under Revision: Foundations of Computational Mathematics
- Berahas, A. S., Cao, L., & Scheinberg, K. (2019). Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise. Under 3rd Round of Review: SIAM Journal on Optimization
- Berahas, A. S., Cao, L., Choromanski, K., & Scheinberg, K. (2019). Linear Interpolation Gives Better Gradients Than Gaussian Smoothing in Derivative-free Optimization. arXiv preprint arXiv:1905.13043.
Lagrange Polynomial OptML 2020 Spring, Lehigh University
Some Gradient Approximation Methods for Derivative Free Optimization INFORMS 2019, Seattle, WA
Comparing Derivative Free Methods INFORMS 2018, Phoenix, AZ