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20212025
most citedConstrained Reinforcement Learning via Dissipative Saddle Flow Dynamics

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

quant-ph2025

Measurement-Incompatibility Constraints for Maximal Randomness

Tianqi Zheng, Yi Li, Yu Xiang +1

Certifying maximal quantum randomness without assumptions about system dimension remains a pivotal challenge for secure communication and foundational studies. Here, we introduce a…

math.OC2024

Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization

Tianqi Zheng, Nicolas Loizou, Pengcheng You +1

Gradient Descent Ascent (GDA) methods for min-max optimization problems typically produce oscillatory behavior that can lead to instability, e.g., in bilinear settings. To address…

eess.SY2023★ 1 cited

Closed-Loop Motion Planning for Differentially Flat Systems: A Time-Varying Optimization Framework

Tianqi Zheng, John W. Simpson-Porco, Enrique Mallada

Motion planning and control are two core components of the robotic autonomy stack. The standard way to combine them uses an offline/open-loop stage, planning, which designs a feasi…

cs.LG2022★ 1 cited

Constrained Reinforcement Learning via Dissipative Saddle Flow Dynamics

Tianqi Zheng, Pengcheng You, Enrique Mallada

In constrained reinforcement learning (C-RL), an agent seeks to learn from the environment a policy that maximizes the expected cumulative reward while satisfying minimum requireme…

math.OC2021

Inner Approximations of the Positive-Semidefinite Cone via Grassmannian Packings

Tianqi Zheng, James Guthrie, Enrique Mallada

We investigate the problem of finding inner ap-proximations of positive semidefinite (PSD) cones. We developa novel decomposition framework of the PSD cone by meansof conical combi…