Core-Halo decomposition separates core updates from overlapping halo reads aligned to operator dependencies, enabling faithful decentralized implementation of fixed-point problems.
Princeton University Press
3 Pith papers cite this work. Polarity classification is still indexing.
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Joint dynamic programming co-optimizes continuous hardware geometry and Bellman-optimal adaptive policies, yielding large gains over baselines in radar POMDPs, qubit sensors, and 90k-pixel photonic metasensors.
Error propagation mitigation in digital twins is cast as an MDP/POMDP with HMM-derived regimes as states, where the MDP policy maximizes reward and the POMDP recovers 95% of that performance.
citing papers explorer
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Core-Halo Decomposition: Decentralizing Large-Scale Fixed-Point Problems
Core-Halo decomposition separates core updates from overlapping halo reads aligned to operator dependencies, enabling faithful decentralized implementation of fixed-point problems.
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Adaptive Sensing beyond Non-Adaptive Information Limits: End-to-End Co-Design of Geometry, Policy, and Inference
Joint dynamic programming co-optimizes continuous hardware geometry and Bellman-optimal adaptive policies, yielding large gains over baselines in radar POMDPs, qubit sensors, and 90k-pixel photonic metasensors.
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Optimal sequential decision-making for error propagation mitigation in digital twins
Error propagation mitigation in digital twins is cast as an MDP/POMDP with HMM-derived regimes as states, where the MDP policy maximizes reward and the POMDP recovers 95% of that performance.