Diffusing-horizon MPC applies exponentially sparse time grids to linear constrained MPC, leveraging exponential sensitivity decay to reduce solve time by two orders of magnitude with 3% cost penalty in an HVAC case study.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
verdicts
UNVERDICTED 4representative citing papers
RESIST achieves algorithmic and statistical convergence guarantees for strongly convex, PL, and nonconvex ERM under MITM attacks via multistep consensus gradient descent plus robust screening.
BlackVIP adapts foundation models via a Coordinator for input-dependent visual prompts and SPSA-GC for gradient estimation, enabling robust transfer on 19 datasets with low memory use and a link to randomized smoothing robustness.
A novel feasible-path method solves optimal power flow in reduced space by directly enforcing power flow equations and softly penalizing operational constraints via Augmented Lagrangian, with GPU acceleration for the reduced Hessian.
citing papers explorer
-
Diffusing-Horizon Model Predictive Control
Diffusing-horizon MPC applies exponentially sparse time grids to linear constrained MPC, leveraging exponential sensitivity decay to reduce solve time by two orders of magnitude with 3% cost penalty in an HVAC case study.
-
RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent
RESIST achieves algorithmic and statistical convergence guarantees for strongly convex, PL, and nonconvex ERM under MITM attacks via multistep consensus gradient descent plus robust screening.
-
Robust Adaptation of Foundation Models with Black-Box Visual Prompting
BlackVIP adapts foundation models via a Coordinator for input-dependent visual prompts and SPSA-GC for gradient estimation, enabling robust transfer on 19 datasets with low memory use and a link to randomized smoothing robustness.
-
A Feasible Reduced Space Method for Real-Time Optimal Power Flow
A novel feasible-path method solves optimal power flow in reduced space by directly enforcing power flow equations and softly penalizing operational constraints via Augmented Lagrangian, with GPU acceleration for the reduced Hessian.