Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception

16 November 2017

Papers citing "Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception"

12 / 12 papers shown

Title
Bayesian Optimization under Stochastic Delayed Feedback Arun Verma Zhongxiang Dai Bryan Kian Hsiang Low 9 12 0 19 Jun 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 11 78 0 26 Oct 2021
Fully probabilistic design for knowledge fusion between Bayesian filters under uniform disturbances L. Pavelková L. Jirsa A. Quinn 11 2 0 22 Sep 2021
Convolutional Normalizing Flows for Deep Gaussian Processes Haibin Yu Dapeng Liu Yizhou Chen K. H. Low Patrick Jaillet BDL 25 6 0 17 Apr 2021
Variational Bayesian Unlearning Q. Nguyen Bryan Kian Hsiang Low Patrick Jaillet BDL MU 27 121 0 24 Oct 2020
Private Outsourced Bayesian Optimization D. Kharkovskii Zhongxiang Dai K. H. Low 12 21 0 24 Oct 2020
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 89 109 0 20 Oct 2020
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games Zhongxiang Dai Yizhou Chen K. H. Low Patrick Jaillet Teck-Hua Ho 6 26 0 30 Jun 2020
Nonmyopic Gaussian Process Optimization with Macro-Actions D. Kharkovskii Chun Kai Ling K. H. Low 4 16 0 22 Feb 2020
Implicit Posterior Variational Inference for Deep Gaussian Processes Haibin Yu Yizhou Chen Zhongxiang Dai K. H. Low Patrick Jaillet 19 42 0 26 Oct 2019
Large-scale Heteroscedastic Regression via Gaussian Process Haitao Liu Yew-Soon Ong Jianfei Cai BDL 21 26 0 03 Nov 2018
Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression Haibin Yu T. Hoang K. H. Low Patrick Jaillet BDL 50 24 0 01 Nov 2017