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Convergence of Gradient-based MAML in LQR
The main objective of this research paper is to investigate the local convergence characteristics of Model-agnostic Meta-learning (MAML) when applied to linear system quadratic optimal control (LQR).
Differentially Private Algorithms for Statistical Verification of Cyber-Physical Systems
We also show that the standard exponential mechanism that randomizes the output of an algorithm to achieve differential privacy fails to do so in the context of sequential algorithms.
Statistically Model Checking PCTL Specifications on Markov Decision Processes via Reinforcement Learning
Probabilistic Computation Tree Logic (PCTL) is frequently used to formally specify control objectives such as probabilistic reachability and safety.
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