Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets

9 August 2023

Papers citing "Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets"

20 / 20 papers shown

Title
Towards Learning Universal Hyperparameter Optimizers with Transformers Yutian Chen Xingyou Song Chansoo Lee Zehao Wang Qiuyi Zhang ... Greg Kochanski Arnaud Doucet MarcÁurelio Ranzato Sagi Perel Nando de Freitas 101 65 0 26 May 2022
Online Decision Transformer Qinqing Zheng Amy Zhang Aditya Grover OffRL 81 209 0 11 Feb 2022
Revisiting Deep Learning Models for Tabular Data Yu. V. Gorishniy Ivan Rubachev Valentin Khrulkov Artem Babenko LMTD 126 772 0 22 Jun 2021
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML Sebastian Pineda Arango H. Jomaa Martin Wistuba Josif Grabocka 78 60 0 11 Jun 2021
Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen Kevin Lu Aravind Rajeswaran Kimin Lee Aditya Grover Michael Laskin Pieter Abbeel A. Srinivas Igor Mordatch OffRL 151 1,660 0 02 Jun 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 65 109 0 24 Feb 2021
Few-Shot Bayesian Optimization with Deep Kernel Surrogates Martin Wistuba Josif Grabocka BDL 96 70 0 19 Jan 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar Karnin ViT LMTD 215 459 0 11 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 682 41,483 0 22 Oct 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 246 451 0 17 Jun 2020
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations Ksenia Korovina Sailun Xu Kirthevasan Kandasamy Willie Neiswanger Barnabás Póczós J. Schneider Eric Xing 103 123 0 05 Aug 2019
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization Michael Volpp Lukas P. Frohlich Kirsten Fischer Andreas Doerr Stefan Falkner Frank Hutter Christian Daniel 94 85 0 04 Apr 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,229 0 11 Oct 2018
Image Transformer Niki Parmar Ashish Vaswani Jakob Uszkoreit Lukasz Kaiser Noam M. Shazeer Alexander Ku Dustin Tran ViT 149 1,687 0 15 Feb 2018
Practical Transfer Learning for Bayesian Optimization Matthias Feurer Benjamin Letham Frank Hutter E. Bakshy 85 35 0 06 Feb 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 805 132,725 0 12 Jun 2017
Stochastic Variational Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 127 268 0 01 Nov 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,427 0 02 Dec 2015
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros N. Satish N. Sundaram Md. Mostofa Ali Patwary P. Prabhat Ryan P. Adams BDL UQCV 95 1,045 0 19 Feb 2015
Scalable Variational Gaussian Process Classification J. Hensman A. G. Matthews Zoubin Ghahramani BDL 81 646 0 07 Nov 2014