Search Results for author: Wenjie Xu

Found 15 papers, 6 papers with code

Principled Preferential Bayesian Optimization

no code implementations8 Feb 2024 Wenjie Xu, Wenbin Wang, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones

We study the problem of preferential Bayesian optimization (BO), where we aim to optimize a black-box function with only preference feedback over a pair of candidate solutions.

Bayesian Optimization Gaussian Processes

Multi-Agent Bayesian Optimization with Coupled Black-Box and Affine Constraints

no code implementations2 Oct 2023 Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones

Additionally, the algorithm guarantees an $\mathcal{O}(N\sqrt{T})$ bound on the cumulative violation for the known affine constraints, where $N$ is the number of agents.

Bayesian Optimization Gaussian Processes

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

no code implementations1 Oct 2023 Wenjie Xu, Bratislav Svetozarevic, Loris Di Natale, Philipp Heer, Colin N Jones

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.

Bayesian Optimization

Bayesian Optimization of Expensive Nested Grey-Box Functions

no code implementations8 Jun 2023 Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones

We consider the problem of optimizing a grey-box objective function, i. e., nested function composed of both black-box and white-box functions.

Bayesian Optimization

Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion

1 code implementation13 May 2023 Wenjie Xu, Ben Liu, Miao Peng, Xu Jia, Min Peng

We train our model with a masking strategy to convert TKGC task into a masked token prediction task, which can leverage the semantic information in pre-trained language models.

Language Modelling Temporal Knowledge Graph Completion

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

1 code implementation12 Apr 2023 Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones

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.

Bayesian Optimization Gaussian Processes

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

no code implementations21 Nov 2022 Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones

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.

SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction

1 code implementation10 Oct 2022 Miao Peng, Ben Liu, Qianqian Xie, Wenjie Xu, Hua Wang, Min Peng

Specifically, we first exploit network schema as the prior constraint to sample negatives and pre-train our model by employing a multi-level contrastive learning method to yield both prior schema and contextual information.

Contrastive Learning Knowledge Graphs +1

Optimizing Two-Truck Platooning with Deadlines

no code implementations4 Oct 2022 Wenjie Xu, Titing Cui, Minghua Chen

The FPTAS can achieve a fuel consumption within a ratio of $(1+\epsilon)$ to the optimal (for any $\epsilon>0$) with a time complexity polynomial in the size of the transportation network and $1/\epsilon$.

Vocal Bursts Valence Prediction

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

no code implementations20 Sep 2022 Wenjie Xu, Yuning Jiang, Emilio T. Maddalena, Colin N. Jones

In this paper, we study the worst-case complexity of the efficient global optimization problem and, in contrast to existing kernel-specific results, we derive a unified lower bound for the complexity of efficient global optimization in terms of the metric entropy of a ball in its corresponding reproducing kernel Hilbert space~(RKHS).

PointSCNet: Point Cloud Structure and Correlation Learning Based on Space Filling Curve-Guided Sampling

1 code implementation21 Feb 2022 Xingye Chen, Yiqi Wu, Wenjie Xu, Jin Li, Huaiyi Dong, Yilin Chen

This paper proposes a point cloud feature extraction network named PointSCNet, to capture the geometrical structure information and local region correlation information of a point cloud.

3D Point Cloud Classification Semantic Segmentation

Recurrent Neural Networks are Universal Filters

no code implementations25 Sep 2019 Wenjie Xu, Xiuqiong Chen, Stephen S.-T. Yau

Another type of popular neural network, deep (feed-forward) neural network has also been successfully applied in different engineering disciplines, whose approximation capability has been well characterized by universal approxi- mation theorem (Hornik et al. (1989), Park & Sandberg (1991), Lu et al. (2017)).

Time Series Analysis

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