Derives ODE limits of Adam-DA showing that first- and second-order momentum parameters reverse their convergence roles in zero-sum games compared to minimization, validated on GAN experiments.
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A reference-decoupled reformulation makes direct data-driven LQT equivalent to certainty-equivalence solutions and supports convergent offline and online DeePO algorithms.
A diameter criterion tied to a potential function certifies convergence of difference inclusions, enabling discrete proofs for first-order optimization methods with diminishing steps.
Derives contraction-based Q-value extensions for exponential utility and proves almost-sure convergence of two-timescale and one-timescale model-free algorithms in discounted MDPs.
A nonlinear observer on SL(3) achieves local exponential convergence for homography estimation by minimizing an image-intensity cost function with explicit non-degeneracy conditions.
DiMS is a physics-inspired dynamical sampler guaranteed to exactly sample reparameterization-invariant minimum level sets in neural network loss landscapes.
Vector-field guidance combined with distance-bearing repulsion and spacing-error velocity control achieves collision-free, uniformly spaced multi-UAV path following with proven convergence.
citing papers explorer
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Direct Data-Driven Linear Quadratic Tracking via Policy Optimization
A reference-decoupled reformulation makes direct data-driven LQT equivalent to certainty-equivalence solutions and supports convergent offline and online DeePO algorithms.
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Equivariant Observer Design on SL(3) for Image Intensity-Based Homography Estimation
A nonlinear observer on SL(3) achieves local exponential convergence for homography estimation by minimizing an image-intensity cost function with explicit non-degeneracy conditions.
- Online Learning-Based Control with Guaranteed Error Bounds for a Class of Nonlinear Systems