104 citations · 256 across the 39 of their papers we have counts for
6 papers · 1 filter
Multi-Agent Bayesian Optimization with Coupled Black-Box and Affine Constraints
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic +1
This paper studies the problem of distributed multi-agent Bayesian optimization with both coupled black-box constraints and known affine constraints. A primal-dual distributed algo…
Federated Linear Bandit Learning via Over-the-Air Computation
Jiali Wang, Yuning Jiang, Xin Liu +2
In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the envi…
Bayesian Optimization of Expensive Nested Grey-Box Functions
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic +1
We consider the problem of optimizing a grey-box objective function, i.e., nested function composed of both black-box and white-box functions. A general formulation for such grey-b…
Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic +1
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 fun…
Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
Wenzhi Fang, Ziyi Yu, Yuning Jiang +3
Federated learning (FL), as an emerging edge artificial intelligence paradigm, enables many edge devices to collaboratively train a global model without sharing their private data.…
Robust Uncertainty Bounds in Reproducing Kernel Hilbert Spaces: A Convex Optimization Approach
Paul Scharnhorst, Emilio T. Maddalena, Yuning Jiang +1
The problem of establishing out-of-sample bounds for the values of an unkonwn ground-truth function is considered. Kernels and their associated Hilbert spaces are the main formalis…