Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel

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Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel

17 January 2025

Richard Cornelius Suwandi

Sergios Theodoridis

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Papers citing "Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel"

16 / 16 papers shown

Title
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 128 0 0 24 Mar 2025
SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting Shengsheng Lin Weiwei Lin Wentai Wu Feiyu Zhao Ruichao Mo Haotong Zhang AI4TS 59 59 0 22 Aug 2023
Long-term Forecasting with TiDE: Time-series Dense Encoder Abhimanyu Das Weihao Kong Andrew B. Leach Shaan Mathur Rajat Sen Rose Yu AI4TS 91 274 0 17 Apr 2023
Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning Arne Schmidt Pablo Morales-Álvarez Rafael Molina 57 13 0 08 Feb 2023
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers Yuqi Nie Nam H. Nguyen Phanwadee Sinthong Jayant Kalagnanam AIFin AI4TS 92 1,406 0 27 Nov 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 111 78 0 28 May 2022
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey Kai Chen Qinglei Kong Yijue Dai Yue Xu Feng Yin Lexi Xu Shuguang Cui 90 30 0 18 Mar 2021
Distributed Online Learning with Multiple Kernels Jeongmin Chae Songnam Hong 63 29 0 17 Nov 2020
Federated Learning With Quantized Global Model Updates M. Amiri Deniz Gunduz Sanjeev R. Kulkarni H. Vincent Poor FedML 92 132 0 18 Jun 2020
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series Feng Yin Lishuo Pan Xinwei He Tianshi Chen Sergios Theodoridis Zhi-Quan Zhi-Quan Luo AI4TS 47 26 0 21 Apr 2019
Wireless Traffic Prediction with Scalable Gaussian Process: Framework, Algorithms, and Verification Yue Xu Feng Yin Wenjun Xu Jiaru Lin Shuguang Cui 72 99 0 13 Feb 2019
Large-scale Heteroscedastic Regression via Gaussian Process Haitao Liu Yew-Soon Ong Jianfei Cai BDL 53 26 0 03 Nov 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 96 693 0 03 Jul 2018
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization G. Scutari Ying Sun 92 63 0 17 May 2018
ADMM Penalty Parameter Selection by Residual Balancing B. Wohlberg 45 64 0 20 Apr 2017
Gaussian Process Kernels for Pattern Discovery and Extrapolation A. Wilson Ryan P. Adams GP 81 609 0 18 Feb 2013