Three Recent Papers
"Analysis of the Frank-Wolfe Method for Convex Composite Optimization involving a Logarithmically-Homogeneous Barrier", with Renbo Zhao, to appear in Mathematical Programming A.
"Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization," with Geoffrey Négiar, Gideon Dresdner, Alicia Yi-Ting Tsai, Laurent El Ghaoui, Francesco Locatello, and Fabian Pedregosa, to appear at International Conference on Machine Learning (ICML) 2020.
"An 'Oblivious' Ellipsoid Algorithm for Solving a System of (In)Feasible Linear Inequalities," with Jourdain Lamperski and Michael Todd, conditionally accepted to Mathematics of Operations Research.
- Nonlinear optimization theory, applications, and computation -- current focus on algorithmic theory and practice of first-order methods
- Computational complexity of nonlinear optimization
- Interior-point methods in convex optimization
- Computational science
- Related mathematical systems
- Applied optimization in management and engineering
- Linear optimization
- Fixed-point methods