Publications by Wenjie Xu | EPFL Graph Search

Bayesian Optimization with Constraints, Structure and Human Feedback

Performance tuning is a pervasive challenge in science and engineering, involving optimization of expensive black-box functions to achieve desired outcomes. This thesis focuses on Bayesian optimization (BO) as a promising solution for addressing the comple ...

EPFL2025

Data-driven adaptive building thermal controller tuning with constraints: A primal-dual contextual Bayesian optimization approach

Colin Neil Jones, Wenjie Xu

We study the problem of tuning the parameters of a room temperature controller to minimize its energy consumption, subject to the constraint that the daily cumulative thermal discomfort of the occupants is below a given threshold. We formulate it as an onl ...

Elsevier Sci Ltd2024

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Colin Neil Jones, Wenjie Xu, Bratislav Svetozarevic

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Elsevier Sci Ltd2024

Lower Bounds on the Noiseless Worst-Case Complexity of Efficient Global Optimization

Colin Neil Jones, Yuning Jiang, Wenjie Xu

Efficient global optimization is a widely used method for optimizing expensive black-box functions. In this paper, we study the worst-case oracle complexity of the efficient global optimization problem. In contrast to existing kernel-specific results, we d ...

2024

Minimizing Emission for Timely Heavy-Duty Truck Transportation

Wenjie Xu

We consider the problem of minimizing emission of a heavy-duty truck transporting freight between two locations subject to a hard deadline constraint. The truck is equipped with a multi-speed transmission and a modern combustion engine that intelligently s ...

IEEE Institute of Electrical and Electronics Engineers2024

Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints

Colin Neil Jones, Yuning Jiang, Wenjie Xu, Bratislav Svetozarevic

This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box functions affected by exogenous time-varying contextual disturbances. A primal- ...

IEEE2023

CONFIG: Constrained Efficient Global Optimization for Closed-Loop Control System Optimization with Unmodeled Constraints

Colin Neil Jones, Yuning Jiang, Wenjie Xu, Bratislav Svetozarevic

In this paper, the CONFIG algorithm, a simple and provably efficient constrained global optimization algorithm, is applied to optimize the closed-loop control performance of an unknown system with unmodeled constraints. Existing Gaussian process based clos ...

Elsevier2023

Ride the Tide of Traffic Conditions: Opportunistic Driving Improves Energy Efficiency of Timely Truck Transportation

Wenjie Xu

We study the problem of minimizing fuel consumption of a heavy-duty truck traveling across the national highway network subject to a hard deadline. We focus on a real-world setting that traversing a road segment is subject to variable speed ranges due to d ...

IEEE Institute of Electrical and Electronics Engineers2023

Optimizing Two-Truck Platooning With Deadlines

Wenjie Xu

We study a transportation problem where two heavy-duty trucks travel across the national highway from separate origins to destinations, subject to individual deadline constraints. Our objective is to minimize their total fuel consumption by jointly optimiz ...

IEEE Institute of Electrical and Electronics Engineers2023

Recurrent Neural Networks Are Universal Approximators With Stochastic Inputs

Wenjie Xu

In this article, we investigate the approximation ability of recurrent neural networks (RNNs) with stochastic inputs in state space model form. More explicitly, we prove that open dynamical systems with stochastic inputs can be well-approximated by a speci ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022