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eess.SY2026
On the Optimization Landscape of Observer-based Dynamic Linear Quadratic Control
Jingliang Duan, Jie Li, Yinsong Ma +5
Understanding the optimization landscape of linear quadratic regulation (LQR) problems is fundamental to the design of efficient reinforcement learning solutions. Recent work has m…
cs.LG2026
One-Step Sampler for Boltzmann Distributions via Drifting
Wenhan Cao, Keyu Yan, Lin Zhao
We present a drifting-based framework for amortized sampling of Boltzmann distributions defined by energy functions. The method trains a one-step neural generator by projecting sam…