1 citations · 2 across the 18 of their papers we have counts for
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H-PDLP: GPU-Accelerated Linear Programming via Generalized PDHG and Homogeneous Self-Dual Embedding
Haihao Lu, Bo Tang
GPU-based first-order methods are emerging as an approach for solving large-scale linear programming (LP) problems. We present H-PDLP, a GPU first-order LP solver based on a genera…
PDNQP: A GPU-based Factorization-free Method for Large-scale Nonconvex Quadratic Programming
Zixi Chen, Haihao Lu
Large-scale nonconvex quadratic programming remains challenging because the sparse matrix factorizations used by many existing solvers can incur substantial computational and memor…
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…
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…
End-to-End Learning of Correlated Operating Reserve Requirements in Security-Constrained Economic Dispatch
Owen Shen, Hung-po Chao, Haihao Lu +1
Operating reserve requirements in security-constrained economic dispatch (SCED) depend strongly on the assumed correlation structure of renewable forecast errors, yet that structur…
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…