Differentially Private Federated Bayesian Optimization with Distributed Exploration

27 October 2021

Papers citing "Differentially Private Federated Bayesian Optimization with Distributed Exploration"

31 / 31 papers shown

Title
$$\texttt{LLINBO}$: Trustworthy LLM-in-the-Loop Bayesian Optimization$ $\texttt{LLINBO}$ : Trustworthy LLM-in-the-Loop Bayesian Optimization Chih-Yu Chang Milad Azvar C. Okwudire Raed Al Kontar UQCV 21 0 0 20 May 2025
Differentially Private Kernelized Contextual Bandits Nikola Pavlovic Sudeep Salgia Qing Zhao 40 1 0 13 Jan 2025
Collaborative and Federated Black-box Optimization: A Bayesian Optimization Perspective Raed Al Kontar FedML 40 1 0 12 Nov 2024
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting Chunlin Tian Li Li Kahou Tam Yebo Wu Chengzhong Xu FedML 34 3 0 12 Oct 2024
Batch Bayesian Optimization for Replicable Experimental Design Zhongxiang Dai Q. Nguyen Sebastian Shenghong Tay Daisuke Urano Richalynn Leong Bryan Kian Hsiang Low Patrick Jaillet 23 4 0 02 Nov 2023
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression Kevin Li Max Balakirsky Simon Mak 27 2 0 23 Oct 2023
Quantum Bayesian Optimization Zhongxiang Dai Gregory Kang Ruey Lau Arun Verma Yao Shu K. H. Low Patrick Jaillet 42 10 0 09 Oct 2023
FedPop: Federated Population-based Hyperparameter Tuning Haokun Chen Denis Krompass Jindong Gu Volker Tresp FedML 38 0 0 16 Aug 2023
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing Jinglong Luo Yehong Zhang Jiaqi Zhang Shuang Qin Haibo Wang Yue Yu Zenglin Xu 51 5 0 26 Jun 2023
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design Xubo Yue Raed Al Kontar A. Berahas Yang Liu Blake N. Johnson 25 4 0 25 Jun 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra Zhongxiang Dai Jasraj Singh See-Kiong Ng K. H. Low AAML 36 6 0 07 Jun 2023
Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles Zhiwei Tang Dmitry Rybin Tsung-Hui Chang ALM DiffM 39 26 0 07 Mar 2023
On Noisy Evaluation in Federated Hyperparameter Tuning Kevin Kuo Pratiksha Thaker M. Khodak John Nguyen Daniel Jiang Ameet Talwalkar Virginia Smith FedML 41 8 0 17 Dec 2022
Federated Learning Hyper-Parameter Tuning from a System Perspective Huan Zhang Lei Fu Mi Zhang Pengfei Hu Xiuzhen Cheng P. Mohapatra Xin Liu FedML 21 7 0 24 Nov 2022
Federated Hypergradient Descent A. K. Kan FedML 42 3 0 03 Nov 2022
A Secure Federated Data-Driven Evolutionary Multi-objective Optimization Algorithm Qiqi Liu Yuping Yan P. Ligeti Yaochu Jin FedML 35 14 0 15 Oct 2022
Sample-Then-Optimize Batch Neural Thompson Sampling Zhongxiang Dai Yao Shu Bryan Kian Hsiang Low Patrick Jaillet AAML 33 24 0 13 Oct 2022
FEATHERS: Federated Architecture and Hyperparameter Search Jonas Seng P. Prasad Martin Mundt Devendra Singh Dhami Kristian Kersting FedML 55 3 0 24 Jun 2022
Bayesian Optimization under Stochastic Delayed Feedback Arun Verma Zhongxiang Dai Bryan Kian Hsiang Low 17 12 0 19 Jun 2022
On Provably Robust Meta-Bayesian Optimization Zhongxiang Dai Yizhou Chen Haibin Yu K. H. Low Patrick Jaillet AAML 28 10 0 14 Jun 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 40 200 0 07 Jun 2022
Federated X-Armed Bandit Wenjie Li Qifan Song Jean Honorio Guang Lin FedML 13 4 0 30 May 2022
Federated Neural Bandits Zhongxiang Dai Yao Shu Arun Verma Flint Xiaofeng Fan Bryan Kian Hsiang Low Patrick Jaillet FedML 35 13 0 28 May 2022
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig FedML 26 6 0 16 Feb 2022
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee Flint Xiaofeng Fan Yining Ma Zhongxiang Dai Wei Jing Cheston Tan K. H. Low FedML AI4CE 19 78 0 26 Oct 2021
Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System Stephan Holly Thomas Hiessl Safoura Rezapour Lakani Daniel Schall C. Heitzinger J. Kemnitz FedML 47 17 0 15 Oct 2021
FedLab: A Flexible Federated Learning Framework Dun Zeng Siqi Liang Xiangjing Hu Hui Wang Zenglin Xu FedML 13 107 0 24 Jul 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Yue Liu Yiqun Diao Quan Chen Bingsheng He FedML OOD 101 955 0 03 Feb 2021
Federated Bandit: A Gossiping Approach Zhaowei Zhu Jingxuan Zhu Ji Liu Yang Liu FedML 152 83 0 24 Oct 2020
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 89 111 0 20 Oct 2020
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 91 278 0 02 Oct 2017