An approximate IPTR framework for linearly constrained optimization uses low-rank projector updates to cut per-iteration cost while preserving feasibility and convergence guarantees, with experiments showing 2.48x speedup.
Cohen, Yin Tat Lee, and Zhao Song,Solving linear programs in the current matrix multipli- cation time, Journal of the ACM (JACM)68(2021), no
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Scalable First-Order Interior Point Trust Region Algorithms for Linearly Constrained Optimization
An approximate IPTR framework for linearly constrained optimization uses low-rank projector updates to cut per-iteration cost while preserving feasibility and convergence guarantees, with experiments showing 2.48x speedup.