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Kang Liu

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Preprint Aug 2026

Residual-Controlled Douglas--Rachford Splitting for Differentiable Solver Layers

Differentiable solver layers embed constrained optimization into end-to-end learning systems, but fixed-depth unrolling must trade off solution quality, feasibility, and computational budget. We propose Residual-Controlled Douglas--Rachford Splitting (RCDRS), a differentiable solver layer for conic linear programs. RCD...

Kang Liu, Jianchen Hu · 1 citation
#machine learning Preprint Sep 2026

Equilibrium bias and convergence in augmented primal--dual dynamics with sampled constraints

This work studies the stability and convergence of augmented primal-dual dynamics when constraint values are estimated from samples. Unbiased constraint observations can produce a biased augmented multiplier signal, shifting the equilibria of the mean dynamics. For componentwise inequalities, we give a necessary and su...

Kang Liu, Meng-Xiao Chen, Si-Qin Xiong et al. · 0 citations

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