ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2003.13826
  4. Cited By
Initial Design Strategies and their Effects on Sequential Model-Based
  Optimization

Initial Design Strategies and their Effects on Sequential Model-Based Optimization

30 March 2020
Jakob Bossek
Carola Doerr
P. Kerschke
ArXivPDFHTML

Papers citing "Initial Design Strategies and their Effects on Sequential Model-Based Optimization"

9 / 9 papers shown
Title
HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks
HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks
Raffaele Mura
Giuseppe Floris
Luca Scionis
Giorgio Piras
Maura Pintor
Ambra Demontis
Giorgio Giacinto
Battista Biggio
Fabio Roli
AAML
58
0
0
11 Jul 2024
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
C. Benjamins
E. Raponi
Anja Jankovic
Carola Doerr
Marius Lindauer
TPM
21
3
0
07 Jun 2023
Towards Automated Design of Bayesian Optimization via Exploratory
  Landscape Analysis
Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis
C. Benjamins
Anja Jankovic
E. Raponi
K. Blom
Marius Lindauer
Carola Doerr
25
5
0
17 Nov 2022
PI is back! Switching Acquisition Functions in Bayesian Optimization
PI is back! Switching Acquisition Functions in Bayesian Optimization
C. Benjamins
E. Raponi
Anja Jankovic
K. Blom
Maria Laura Santoni
Marius Lindauer
Carola Doerr
38
5
0
02 Nov 2022
Faster variational quantum algorithms with quantum kernel-based
  surrogate models
Faster variational quantum algorithms with quantum kernel-based surrogate models
Alistair W. R. Smith
A. Paige
Myungshik S. Kim
20
4
0
02 Nov 2022
Multi-Objective Hyperparameter Optimization in Machine Learning -- An
  Overview
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview
Florian Karl
Tobias Pielok
Julia Moosbauer
Florian Pfisterer
Stefan Coors
...
Jakob Richter
Michel Lang
Eduardo C. Garrido-Merchán
Juergen Branke
B. Bischl
AI4CE
26
56
0
15 Jun 2022
A Collection of Deep Learning-based Feature-Free Approaches for
  Characterizing Single-Objective Continuous Fitness Landscapes
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes
M. Seiler
Raphael Patrick Prager
P. Kerschke
Heike Trautmann
30
20
0
12 Apr 2022
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and
  Open Challenges
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
B. Bischl
Martin Binder
Michel Lang
Tobias Pielok
Jakob Richter
...
Theresa Ullmann
Marc Becker
A. Boulesteix
Difan Deng
Marius Lindauer
85
448
0
13 Jul 2021
Variance Reduction for Better Sampling in Continuous Domains
Variance Reduction for Better Sampling in Continuous Domains
Laurent Meunier
Carola Doerr
Jérémy Rapin
O. Teytaud
17
8
0
24 Apr 2020
1