ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2012.06932
  4. Cited By
Warm Starting CMA-ES for Hyperparameter Optimization

Warm Starting CMA-ES for Hyperparameter Optimization

AAAI Conference on Artificial Intelligence (AAAI), 2020
13 December 2020
Masahiro Nomura
Shuhei Watanabe
Youhei Akimoto
Yoshihiko Ozaki
Masaki Onishi
ArXiv (abs)PDFHTML

Papers citing "Warm Starting CMA-ES for Hyperparameter Optimization"

21 / 21 papers shown
Enhanced Ideal Objective Vector Estimation for Evolutionary Multi-Objective Optimization
Enhanced Ideal Objective Vector Estimation for Evolutionary Multi-Objective Optimization
Ruihao Zheng
Zhenkun Wang
Yin Wu
Maoguo Gong
188
0
0
28 May 2025
Warm Starting of CMA-ES for Contextual Optimization Problems
Warm Starting of CMA-ES for Contextual Optimization ProblemsParallel Problem Solving from Nature (PPSN), 2025
Yuta Sekino
Kento Uchida
Shinichi Shirakawa
350
1
0
18 Feb 2025
Learning Evolution via Optimization Knowledge Adaptation
Learning Evolution via Optimization Knowledge Adaptation
Chao Wang
Licheng Jiao
Jiaxuan Zhao
Lingling Li
Fang Liu
Steve Yang
KELM
344
1
0
04 Jan 2025
Knowledge-aware Evolutionary Graph Neural Architecture Search
Knowledge-aware Evolutionary Graph Neural Architecture SearchKnowledge-Based Systems (KBS), 2024
Chao Wang
Jiaxuan Zhao
Lingling Li
Licheng Jiao
Fang Liu
Xu Liu
Steve Yang
421
11
0
26 Nov 2024
Hyperparameter Optimization Can Even be Harmful in Off-Policy Learning
  and How to Deal with It
Hyperparameter Optimization Can Even be Harmful in Off-Policy Learning and How to Deal with It
Yuta Saito
Masahiro Nomura
OffRL
354
5
0
23 Apr 2024
High-dimensional Bayesian Optimization via Covariance Matrix Adaptation
  Strategy
High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
Lam Ngo
Huong Ha
Jeffrey Chan
Vu-Linh Nguyen
Hongyu Zhang
230
7
0
05 Feb 2024
cmaes: A Simple yet Practical Python Library for CMA-ES
cmaes: A Simple yet Practical Python Library for CMA-ES
Masahiro Nomura
Masashi Shibata
Ryoki Hamano
420
51
0
02 Feb 2024
A Consistent Lebesgue Measure for Multi-label Learning
A Consistent Lebesgue Measure for Multi-label Learning
Kaan Demir
B. Nguyen
Bing Xue
Mengjie Zhang
254
1
0
01 Feb 2024
A Lightweight and Transferable Design for Robust LEGO Manipulation
A Lightweight and Transferable Design for Robust LEGO Manipulation
Ruixuan Liu
Yifan Sun
Changliu Liu
415
12
0
05 Sep 2023
CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and
  Salvageable Failure
CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure
Lennart Purucker
Joeran Beel
260
11
0
01 Jul 2023
Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance
Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance
Shuhei Watanabe
633
336
0
21 Apr 2023
Speeding Up Multi-Objective Hyperparameter Optimization by Task
  Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen EstimatorInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Shuhei Watanabe
Noor H. Awad
Masaki Onishi
Katharina Eggensperger
447
20
0
13 Dec 2022
Adaptive Scenario Subset Selection for Worst-Case Optimization and its
  Application to Well Placement Optimization
Adaptive Scenario Subset Selection for Worst-Case Optimization and its Application to Well Placement OptimizationApplied Soft Computing (ASC), 2022
Atsuhiro Miyagi
Kazuto Fukuchi
Jun Sakuma
Youhei Akimoto
193
2
0
29 Nov 2022
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
Xuan Rao
Bo Zhao
Xiaosong Yi
358
5
0
11 Nov 2022
Hyperparameter Tuning in Echo State Networks
Hyperparameter Tuning in Echo State NetworksAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2022
Filip Matzner
215
7
0
16 Jul 2022
Complete Inertial Pose Dataset: from raw measurements to pose with
  low-cost and high-end MARG sensors
Complete Inertial Pose Dataset: from raw measurements to pose with low-cost and high-end MARG sensors
M. Palermo
Sara M. Cerqueira
J. André
António Pereira
C. Santos
180
1
0
12 Feb 2022
Fast Moving Natural Evolution Strategy for High-Dimensional Problems
Fast Moving Natural Evolution Strategy for High-Dimensional ProblemsIEEE Congress on Evolutionary Computation (CEC), 2022
Masahiro Nomura
I. Ono
344
9
0
27 Jan 2022
AutoMC: Automated Model Compression based on Domain Knowledge and
  Progressive search strategy
AutoMC: Automated Model Compression based on Domain Knowledge and Progressive search strategyIEEE International Conference on Data Engineering (ICDE), 2022
Chunnan Wang
Hongzhi Wang
Xiangyu Shi
174
1
0
24 Jan 2022
Natural Evolution Strategy for Unconstrained and Implicitly Constrained
  Problems with Ridge Structure
Natural Evolution Strategy for Unconstrained and Implicitly Constrained Problems with Ridge Structure
Masahiro Nomura
I. Ono
224
3
0
21 Aug 2021
Which Hyperparameters to Optimise? An Investigation of Evolutionary
  Hyperparameter Optimisation in Graph Neural Network For Molecular Property
  Prediction
Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction
Yingfang Yuan
Wenjun Wang
Wei Pang
235
7
0
13 Apr 2021
Efficient Hyperparameter Optimization under Multi-Source Covariate Shift
Efficient Hyperparameter Optimization under Multi-Source Covariate Shift
Masahiro Nomura
Yuta Saito
207
9
0
18 Jun 2020
1
Page 1 of 1