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#machine learning Preprint Sep 2026

DCEmbed: Scalable Optimization over Neural Surrogates

DCEmbed is proposed, a heuristic for optimization problems with embedded neural surrogates that leverages the difference-of-convex (DC) representation of the network and avoids adding activation binaries, and demonstrates much faster progress toward high-quality feasible solutions than approaches using exact mixed-inte...

Akshay Sreekumar, Nicolas H. Christianson, P. Donti et al. · 0 citations
#machine learning Preprint Aug 2026

Scalable Self-Supervised Learning for Multiphase AC-OPF in Distribution Systems with Topology Reconfiguration

The Penalty + Sequential Linearized Feasibility Seeking (SLFS) algorithm is presented, a self-supervised learning framework for multiphase distribution AC-OPF under switch-induced topology changes, demonstrating a viable path toward real-time, topology-aware AC-OPF for large-scale distribution grids.

H. Nguyen, Shao-Hui Liu, R. Biswas et al. · 0 citations

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