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Robust Gaussian Processes via Relevance Pursuit

8 January 2025

Papers citing "Robust Gaussian Processes via Relevance Pursuit"

23 / 23 papers shown

Title
Unexpected Improvements to Expected Improvement for Bayesian Optimization Sebastian Ament Sam Daulton David Eriksson Maximilian Balandat E. Bakshy 80 80 0 08 Jan 2025
Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure Jihao Andreas Lin Sebastian Ament Maximilian Balandat E. Bakshy BDL 52 2 0 11 Oct 2024
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 71 13 0 01 Nov 2023
Self-Correcting Bayesian Optimization through Bayesian Active Learning Carl Hvarfner E. Hellsten Frank Hutter Luigi Nardi GP 70 16 0 21 Apr 2023
Robust Gaussian Process Regression with Huber Likelihood Pooja Algikar L. Mili GP 22 10 0 19 Jan 2023
Discovering Many Diverse Solutions with Bayesian Optimization Natalie Maus Kaiwen Wu David Eriksson Jacob R. Gardner 63 25 0 20 Oct 2022
Bayesian Active Learning with Fully Bayesian Gaussian Processes Christoffer Riis Francisco Antunes F. B. Hüttel C. L. Azevedo Francisco Câmara Pereira GP 75 24 0 20 May 2022
Sparse Bayesian Learning via Stepwise Regression Sebastian Ament Carla P. Gomes 50 6 0 11 Jun 2021
On the Optimality of Backward Regression: Sparse Recovery and Subset Selection Sebastian Ament Carla P. Gomes 34 6 0 06 Jun 2021
Robust Gaussian Process Regression Based on Iterative Trimming Zhaozhou Li Lu Li Z. Shao 18 23 0 22 Nov 2020
Robust Gaussian Process Regression with a Bias Model Chiwoo Park David J. Borth Nicholas S. Wilson Chad N. Hunter F. Friedersdorf 53 28 0 14 Jan 2020
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob R. Gardner Geoff Pleiss D. Bindel Kilian Q. Weinberger A. Wilson GP 136 1,100 0 28 Sep 2018
A Tutorial on Bayesian Optimization P. Frazier GP 111 1,788 0 08 Jul 2018
On Matching Pursuit and Coordinate Descent Francesco Locatello Anant Raj Sai Praneeth Karimireddy Gunnar Rätsch Bernhard Schölkopf Sebastian U. Stich Martin Jaggi 39 23 0 26 Mar 2018
Scalable Log Determinants for Gaussian Process Kernel Learning Kun Dong David Eriksson H. Nickisch D. Bindel A. Wilson 53 95 0 09 Nov 2017
Robust Bayesian Optimization with Student-t Likelihood Ruben Martinez-Cantin M. McCourt K. Tee 29 6 0 18 Jul 2017
Batched Large-scale Bayesian Optimization in High-dimensional Spaces Zi Wang Clement Gehring Pushmeet Kohli Stefanie Jegelka UQCV 54 214 0 05 Jun 2017
A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe Francesco Locatello Rajiv Khanna Michael Tschannen Martin Jaggi 50 50 0 21 Feb 2017
Restricted Strong Convexity Implies Weak Submodularity Ethan R. Elenberg Rajiv Khanna A. Dimakis S. Negahban 68 159 0 02 Dec 2016
Accurate and efficient numerical calculation of stable densities via optimized quadrature and asymptotics Sebastian Ament M. O’Neil 90 22 0 14 Jul 2016
Student-t Processes as Alternatives to Gaussian Processes Amar Shah A. Wilson Zoubin Ghahramani GP 90 203 0 18 Feb 2014
Near-optimal Nonmyopic Value of Information in Graphical Models Andreas Krause Carlos Guestrin 79 467 0 04 Jul 2012
Gaussian Process Regression with a Student-t Likelihood Pasi Jylänki J. Vanhatalo Aki Vehtari GP 95 165 0 22 Jun 2011