5 papers
Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning
Wentao Zhang, Wentao Mo
Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Information (peak AoI, also abbrev…
Data-Dependent Regret and Polyak Corrections for Constrained Online Convex Optimization
Wentao Zhang
Constrained online convex optimization requires minimizing regret against adversarial convex costs while satisfying a convex constraint at every round, as needed in safety-critical…
Noise-Adaptive High-Probability Regret Bounds for Online Convex Optimization
Wentao Zhang, Yutong Zhang, Wentao Mo
We study high-probability regret bounds for online convex optimization (OCO) with strongly convex losses and establish three results that resolve open questions at the intersection…
Universal Smoothness via Bernstein Polynomials: A Constructive Approximation Approach for Activation Functions
Wentao Zhang, Yutong Zhang, Yifan Zhu +1
The efficacy of deep neural networks is heavily reliant on the design of non-linear activation functions, yet existing approaches often struggle to balance optimization stability w…
From Knowing to Doing Precisely: A General Self-Correction and Termination Framework for VLA models
Wentao Zhang, Aolan Sun, Wentao Mo +3
While vision-language-action (VLA) models for embodied agents integrate perception, reasoning, and control, they remain constrained by two critical weaknesses: first, during graspi…