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06/08/2023
Bayesian Optimization of Expensive Nested Grey-Box Functions
We consider the problem of optimizing a grey-box objective function, i.e...
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04/12/2023
Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints
This paper studies the problem of online performance optimization of con...
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02/08/2023
Comparison of behavioral systems theory and conventional linear models for predicting building zone temperature in long-term in situ measurements
The potential of Model Predictive Control in buildings has been shown ma...
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01/28/2023
Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints
We study the problem of performance optimization of closed-loop control ...
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11/30/2022
Efficient Reinforcement Learning (ERL): Targeted Exploration Through Action Saturation
Reinforcement Learning (RL) generally suffers from poor sample complexit...
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11/21/2022
CONFIG: Constrained Efficient Global Optimization for Closed-Loop Control System Optimization with Unmodeled Constraints
In this paper, the CONFIG algorithm, a simple and provably efficient con...
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11/11/2022
Physically Consistent Neural ODEs for Learning Multi-Physics Systems
Despite the immense success of neural networks in modeling system dynami...
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09/20/2022
Lower Bounds on the Worst-Case Complexity of Efficient Global Optimization
Efficient global optimization is a widely used method for optimizing exp...
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06/27/2022
Stability Verification of Neural Network Controllers using Mixed-Integer Programming
We propose a framework for the stability verification of Mixed-Integer L...
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05/31/2022
Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning
This manuscript offers the perspective of experimentalists on a number o...
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03/29/2022
Over-the-Air Federated Learning via Second-Order Optimization
Federated learning (FL) is a promising learning paradigm that can tackle...
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03/10/2022
Near-optimal Deep Reinforcement Learning Policies from Data for Zone Temperature Control
Replacing poorly performing existing controllers with smarter solutions ...
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01/24/2022
Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
Federated learning (FL), as an emerging edge artificial intelligence par...
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12/06/2021
Physically Consistent Neural Networks for building thermal modeling: theory and analysis
Due to their high energy intensity, buildings play a major role in the c...
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10/14/2021
VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints
We study the problem of performance optimization of closed-loop control ...
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04/19/2021
Robust Uncertainty Bounds in Reproducing Kernel Hilbert Spaces: A Convex Optimization Approach
Let a labeled dataset be given with scattered samples and consider the h...
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08/10/2020
