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09/09/2023
Global Convergence of Receding-Horizon Policy Search in Learning Estimator Designs
We introduce the receding-horizon policy gradient (RHPG) algorithm, the ...
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01/30/2023
Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning
Many real-world domains require safe decision making in the presence of ...
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04/27/2022
Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization
The design automation of analog circuits is a longstanding challenge. Th...
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02/26/2022
Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning
The design automation of analog circuits is a longstanding challenge in ...
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08/05/2021
Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty
Safety and robustness are two desired properties for any reinforcement l...
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10/10/2020
Robust Constrained-MDPs: Soft-Constrained Robust Policy Optimization under Model Uncertainty
In this paper, we focus on the problem of robustifying reinforcement lea...
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10/06/2020
Optimizing Deep Neural Networks via Discretization of Finite-Time Convergent Flows
In this paper, we investigate in the context of deep neural networks, th...
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05/12/2020
Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization
Data generated from dynamical systems with unknown dynamics enable the l...
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01/22/2020
Local Policy Optimization for Trajectory-Centric Reinforcement Learning
The goal of this paper is to present a method for simultaneous trajector...
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12/18/2019