8 papers · 1 filter
On the Local Linear Convergence of Operator Splitting Methods for Conic Programming
Lijun Ding, Haihao Lu, Jinwen Yang
Operator-splitting methods such as the primal-dual hybrid gradient method (PDHG) and the alternating direction method of multipliers (ADMM) often exhibit linear convergence on coni…
On the Complexity of BFGS Method for Smooth Convex Optimization
Lijun Ding, Jinwen Yang, Baoyu Zhou
We study the BFGS method with an Armijo-Wolfe line search for minimizing convex functions with Lipschitz-continuous gradients, without assuming strong convexity. We establish a glo…
FlashFolio: A GPU-Accelerated Solver for Portfolio Optimization
Yilun Jiang, Haihao Lu, Zedong Peng +1
We present FlashFolio, a GPU-accelerated solver for single-period and multi-period portfolio optimization with factor-based risk modeling, bid-offer spread costs, and nonlinear mar…
Active set identification and rapid convergence for degenerate primal-dual problems
Mateo Díaz, Pedro Izquierdo Lehmann, Haihao Lu +1
Primal-dual methods for solving convex optimization problems with functional constraints often exhibit a distinct two-stage behavior. Initially, they converge towards a solution at…
cuPDLPx: A Further Enhanced GPU-Based First-Order Solver for Linear Programming
Haihao Lu, Zedong Peng, Jinwen Yang
We introduce cuPDLPx, a further enhanced GPU-based first-order solver for linear programming. Building on the recently developed restarted Halpern PDHG for LP, cuPDLPx incorporates…
An Overview of GPU-based First-Order Methods for Linear Programming and Extensions
Haihao Lu, Jinwen Yang
The rapid progress in GPU computing has revolutionized many fields, yet its potential in mathematical programming, such as linear programming (LP), has only recently begun to be re…