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ORCIDYouhei Akimoto
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2020 – today
- 2024
[j20]Youhei Akimoto:
Analysis of Surrogate-Assisted Information-Geometric Optimization Algorithms. Algorithmica 86(1): 33-63 (2024)- [j19]Daiki Morinaga
, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Convergence Rate of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions. IEEE Trans. Evol. Comput. 28(2): 501-515 (2024) - [c76]Daiki Morinaga, Youhei Akimoto:
Sign-Averaging Covariance Matrix Adaptation Evolution Strategy. GECCO 2024 - [c75]Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Linear Convergence Rate Analysis of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions. GECCO Companion 2024: 49-50 - [c74]Youhei Akimoto, Shinichi Shirakawa:
Analysis of Search Space Design for Neural Architecture Search with Weight Sharing. IJCNN 2024: 1-8 - [i43]Daiki Morinaga, Youhei Akimoto:
Theoretical Analysis of Explicit Averaging and Novel Sign Averaging in Comparison-Based Search. CoRR abs/2401.14014 (2024) - [i42]Masahiro Nomura, Youhei Akimoto, Isao Ono:
CMA-ES with Learning Rate Adaptation. CoRR abs/2401.15876 (2024) - [i41]Amane Sakanashi, Rin Suyama, Atsuo Maki, Youhei Akimoto:
Simultaneous optimization of control gains and reference filter coefficients for trajectory tracking control. CoRR abs/2407.05665 (2024) - [i40]Ryoki Hamano, Kento Uchida, Shinichi Shirakawa, Daiki Morinaga, Youhei Akimoto:
Tail Bounds on the Runtime of Categorical Compact Genetic Algorithm. CoRR abs/2407.07388 (2024) - [i39]Kouki Wakita, Fuyuki Hane, Takeshi Sekiguchi, Shigehito Shimizu, Shinji Mitani, Youhei Akimoto, Atsuo Maki:
Conceptual Design on the Field of View of Celestial Navigation Systems for Maritime Autonomous Surface Ships. CoRR abs/2408.15765 (2024) - 2023
- [j18]Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Adaptive scenario subset selection for worst-case optimization and its application to well placement optimization. Appl. Soft Comput. 133: 109842 (2023) - [j17]Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
CAMRI Loss: Improving the Recall of a Specific Class without Sacrificing Accuracy. IEICE Trans. Inf. Syst. 106(4): 523-537 (2023) - [j16]Kotaro Sakamoto, Hideaki Ishibashi, Rei Sato, Shinichi Shirakawa, Youhei Akimoto, Hideitsu Hino:
ATNAS: Automatic Termination for Neural Architecture Search. Neural Networks 166: 446-458 (2023) - [j15]Jiayang Liu, Weiming Zhang, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Unauthorized AI cannot recognize me: Reversible adversarial example. Pattern Recognit. 134: 109048 (2023) - [j14]Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and Its Application to Berthing Control Tasks. ACM Trans. Evol. Learn. Optim. 3(2): 8:1-8:32 (2023) - [j13]Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Statistically Significant Pattern Mining With Ordinal Utility. IEEE Trans. Knowl. Data Eng. 35(9): 8770-8783 (2023) - [c73]Yoshimasa Akimoto, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Privformer: Privacy-preserving Transformer with MPC. EuroS&P 2023: 392-410 - [c72]Masahiro Nomura, Youhei Akimoto, Isao Ono:
CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems? GECCO 2023: 839-847 - [c71]Youhei Akimoto, Nikolaus Hansen:
CMA-ES and Advanced Adaptation Mechanisms. GECCO Companion 2023: 1157-1182 - [c70]Hinata Edo, Yoshiki Miyauchi, Atsuo Maki, Youhei Akimoto:
Trade-off Between Robustness and Worst-Case Performance in Min-Max Optimization. GECCO 2023: 1339-1347 - [c69]Kaiwen Xu, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs. IJCAI 2023: 519-526 - [i38]Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning. CoRR abs/2301.13343 (2023) - [i37]Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and its Application to Berthing Control Tasks. CoRR abs/2303.16079 (2023) - [i36]Masahiro Nomura, Youhei Akimoto, Isao Ono:
CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems? CoRR abs/2304.03473 (2023) - [i35]Kaiwen Xu, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs. CoRR abs/2305.18362 (2023) - [i34]Kouki Wakita, Yoshiki Miyauchi, Youhei Akimoto, Atsuo Maki:
Data Augmentation Methods of Parameter Identification of a Dynamic Model for Harbor Maneuvers. CoRR abs/2305.18851 (2023) - [i33]Keita Saito, Akifumi Wachi, Koki Wataoka, Youhei Akimoto:
Verbosity Bias in Preference Labeling by Large Language Models. CoRR abs/2310.10076 (2023) - 2022
- [j12]Yu Zhe, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Domain Generalization via Adversarially Learned Novel Domains. IEEE Access 10: 101855-101868 (2022) - [j11]Naoki Sakamoto, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Explicitly Constrained Black-Box Optimization With Disconnected Feasible Domains Using Deep Generative Models. IEEE Access 10: 117501-117514 (2022) - [j10]Naoki Sakamoto, Youhei Akimoto:
Adaptive Ranking-Based Constraint Handling for Explicitly Constrained Black-Box Optimization. Evol. Comput. 30(4): 503-529 (2022) - [j9]Youhei Akimoto, Anne Auger, Tobias Glasmachers, Daiki Morinaga:
Global Linear Convergence of Evolution Strategies on More than Smooth Strongly Convex Functions. SIAM J. Optim. 32(2): 1402-1429 (2022) - [j8]Youhei Akimoto, Yoshiki Miyauchi, Atsuo Maki:
Saddle Point Optimization with Approximate Minimization Oracle and Its Application to Robust Berthing Control. ACM Trans. Evol. Learn. Optim. 2(1): 2:1-2:32 (2022) - [c68]Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Unsupervised Causal Binary Concepts Discovery with VAE for Black-Box Model Explanation. AAAI 2022: 9614-9622 - [c67]Ryoji Tanabe, Youhei Akimoto, Ken Kobayashi, Hiroshi Umeki, Shinichi Shirakawa, Naoki Hamada:
A two-phase framework with a bézier simplex-based interpolation method for computationally expensive multi-objective optimization. GECCO 2022: 601-610 - [c66]Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximation. GECCO 2022: 823-831 - [c65]Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. GECCO Companion 2022: 1243-1268 - [c64]Youhei Akimoto:
Monotone improvement of information-geometric optimization algorithms with a surrogate function. GECCO 2022: 1354-1362 - [c63]Yasen Wang, Youhei Akimoto:
On the effect of the sampling ratio of past trajectories in the combination of evolutionary algorithm and deep reinforcement learning. GECCO Companion 2022: 1979-1983 - [c62]Yu Zhe, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Domain Generalization Via Adversarially Learned Novel Domains. ICME 2022: 1-6 - [c61]Syou Hirofumi, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Did You Use My GAN to Generate Fake? Post-hoc Attribution of GAN Generated Images via Latent Recovery. IJCNN 2022: 1-8 - [c60]Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy. IJCNN 2022: 1-8 - [c59]Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning. IJCNN 2022: 1-10 - [c58]Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification. NeurIPS 2022 - [i32]Ryoji Tanabe, Youhei Akimoto, Ken Kobayashi, Hiroshi Umeki, Shinichi Shirakawa, Naoki Hamada:
A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization. CoRR abs/2203.15292 (2022) - [i31]Youhei Akimoto:
Monotone Improvement of Information-Geometric Optimization Algorithms with a Surrogate Function. CoRR abs/2204.02638 (2022) - [i30]Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Black-Box Min-Max Continuous Optimization Using CMA-ES with Worst-case Ranking Approximation. CoRR abs/2204.02646 (2022) - [i29]Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy. CoRR abs/2209.10920 (2022) - [i28]Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Convergence rate of the (1+1)-evolution strategy on locally strongly convex functions with lipschitz continuous gradient and their monotonic transformations. CoRR abs/2209.12467 (2022) - [i27]Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification. CoRR abs/2211.03413 (2022) - [i26]Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Adaptive Scenario Subset Selection for Worst-Case Optimization and its Application to Well Placement Optimization. CoRR abs/2211.16574 (2022) - [i25]Kouki Wakita, Youhei Akimoto, Dimas M. Rachman, Yoshiki Miyauchi, Umeda Naoya, Atsuo Maki:
Collision probability reduction method for tracking control in automatic docking / berthing using reinforcement learning. CoRR abs/2212.06415 (2022) - 2021
- [c57]Masahiro Nomura, Shuhei Watanabe, Youhei Akimoto, Yoshihiko Ozaki, Masaki Onishi:
Warm Starting CMA-ES for Hyperparameter Optimization. AAAI 2021: 9188-9196 - [c56]Rei Sato, Jun Sakuma, Youhei Akimoto:
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment. AAAI 2021: 9489-9496 - [c55]Youhei Akimoto:
Saddle point optimization with approximate minimization oracle. GECCO 2021: 493-501 - [c54]Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. GECCO Companion 2021: 636-663 - [c53]Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Adaptive scenario subset selection for min-max black-box continuous optimization. GECCO 2021: 697-705 - [c52]Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Level generation for angry birds with sequential VAE and latent variable evolution. GECCO 2021: 1052-1060 - [c51]Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Convergence rate of the (1+1)-evolution strategy with success-based step-size adaptation on convex quadratic functions. GECCO 2021: 1169-1177 - [c50]Youhei Akimoto:
Black-Box Min-Max Optimization using CMA-ES. ITAT 2021: 18 - [i24]Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions. CoRR abs/2103.01578 (2021) - [i23]Youhei Akimoto:
Saddle Point Optimization with Approximate Minimization Oracle. CoRR abs/2103.15985 (2021) - [i22]Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Level Generation for Angry Birds with Sequential VAE and Latent Variable Evolution. CoRR abs/2104.06106 (2021) - [i21]Youhei Akimoto, Yoshiki Miyauchi, Atsuo Maki:
Saddle Point Optimization with Approximate Minimization Oracle and its Application to Robust Berthing Control. CoRR abs/2105.11586 (2021) - [i20]Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation. CoRR abs/2109.04518 (2021) - [i19]Kouki Wakita, Atsuo Maki, Umeda Naoya, Yoshiki Miyauchi, Tohga Shimoji, Dimas M. Rachman, Youhei Akimoto:
On Neural Network Identification for Low-Speed Ship Maneuvering Model. CoRR abs/2111.06120 (2021) - [i18]Yoshiki Miyauchi, Atsuo Maki, Naoya Umeda, Dimas M. Rachman, Youhei Akimoto:
System Parameter Exploration of Ship Maneuvering Model for Automatic Docking / Berthing using CMA-ES. CoRR abs/2111.06124 (2021) - 2020
- [j7]Youhei Akimoto, Nikolaus Hansen:
Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies. Evol. Comput. 28(3): 405-435 (2020) - [j6]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Quality gain analysis of the weighted recombination evolution strategy on general convex quadratic functions. Theor. Comput. Sci. 832: 42-67 (2020) - [j5]Kento Uchida, Shinichi Shirakawa, Youhei Akimoto:
Finite-Sample Analysis of Information Geometric Optimization With Isotropic Gaussian Distribution on Convex Quadratic Functions. IEEE Trans. Evol. Comput. 24(6): 1035-1049 (2020) - [c49]Hiromu Yakura, Youhei Akimoto, Jun Sakuma:
Generate (Non-Software) Bugs to Fool Classifiers. AAAI 2020: 1070-1078 - [c48]Naoki Sakamoto, Eiji Semmatsu, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Deep generative model for non-convex constraint handling. GECCO 2020: 636-644 - [c47]Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Statistically Significant Pattern Mining with Ordinal Utility. KDD 2020: 1645-1655 - [c46]Youhei Akimoto, Naoki Sakamoto, Makoto Ohtani:
Multi-fidelity Optimization Approach Under Prior and Posterior Constraints and Its Application to Compliance Minimization. PPSN (1) 2020: 81-94 - [i17]Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Statistically Significant Pattern Mining with Ordinal Utility. CoRR abs/2008.10747 (2020) - [i16]Youhei Akimoto, Anne Auger, Tobias Glasmachers, Daiki Morinaga:
Global Linear Convergence of Evolution Strategies on More Than Smooth Strongly Convex Functions. CoRR abs/2009.08647 (2020) - [i15]Rei Sato, Jun Sakuma, Youhei Akimoto:
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment. CoRR abs/2012.06138 (2020) - [i14]Masahiro Nomura, Shuhei Watanabe, Youhei Akimoto, Yoshihiko Ozaki, Masaki Onishi:
Warm Starting CMA-ES for Hyperparameter Optimization. CoRR abs/2012.06932 (2020)
2010 – 2019
- 2019
- [c45]Daiki Morinaga, Youhei Akimoto:
Generalized drift analysis in continuous domain: linear convergence of (1 + 1)-ES on strongly convex functions with Lipschitz continuous gradients. FOGA 2019: 13-24 - [c44]Naoki Sakamoto, Youhei Akimoto:
Adaptive ranking based constraint handling for explicitly constrained black-box optimization. GECCO 2019: 700-708 - [c43]Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. GECCO (Companion) 2019: 837-861 - [c42]Youhei Akimoto, Takuma Shimizu, Takahiro Yamaguchi:
Adaptive objective selection for multi-fidelity optimization. GECCO 2019: 880-888 - [c41]Atsuhiro Miyagi, Youhei Akimoto, Hajime Yamamoto:
Well placement optimization under geological statistical uncertainty. GECCO 2019: 1284-1292 - [c40]Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari, Kento Uchida, Shota Saito, Kouhei Nishida:
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search. ICML 2019: 171-180 - [i13]Youhei Akimoto, Nikolaus Hansen:
Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies. CoRR abs/1905.05885 (2019) - [i12]Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari, Kento Uchida, Shota Saito, Kouhei Nishida:
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search. CoRR abs/1905.08537 (2019) - [i11]Hiromu Yakura, Youhei Akimoto, Jun Sakuma:
Generate (non-software) Bugs to Fool Classifiers. CoRR abs/1911.08644 (2019) - 2018
- [c39]Shinichi Shirakawa, Yasushi Iwata, Youhei Akimoto:
Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling. AAAI 2018: 4074-4082 - [c38]Takahiro Yamaguchi, Youhei Akimoto:
A note on the CMA-ES for functions with periodic variables. GECCO (Companion) 2018: 227-228 - [c37]Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. GECCO (Companion) 2018: 720-744 - [c36]Youhei Akimoto, Anne Auger, Tobias Glasmachers:
Drift theory in continuous search spaces: expected hitting time of the (1 + 1)-ES with 1/5 success rule. GECCO 2018: 801-808 - [c35]Kouhei Nishida, Youhei Akimoto:
PSA-CMA-ES: CMA-ES with population size adaptation. GECCO 2018: 865-872 - [c34]Kento Uchida, Shinichi Shirakawa, Youhei Akimoto:
Analysis of information geometric optimization with isotropic gaussian distribution under finite samples. GECCO 2018: 897-904 - [c33]Kyotaro Ohashi, Natsuki Fujiyoshi, Naoki Sakamoto, Youhei Akimoto:
Model parameter adaptive instance-based policy optimization for episodic control tasks of nonholonomic systems. GECCO (Companion) 2018: 1426-1433 - [c32]Kouhei Nishida, Youhei Akimoto:
Benchmarking the PSA-CMA-ES on the BBOB noiseless testbed. GECCO (Companion) 2018: 1529-1536 - [c31]Atsuhiro Miyagi, Youhei Akimoto, Hajime Yamamoto:
Well placement optimization for carbon dioxide capture and storage via CMA-ES with mixed integer support. GECCO (Companion) 2018: 1696-1703 - [c30]Shota Saito, Shinichi Shirakawa, Youhei Akimoto:
Embedded feature selection using probabilistic model-based optimization. GECCO (Companion) 2018: 1922-1925 - [i10]Shinichi Shirakawa, Yasushi Iwata, Youhei Akimoto:
Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling. CoRR abs/1801.07650 (2018) - [i9]Youhei Akimoto, Anne Auger, Tobias Glasmachers:
Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule. CoRR abs/1802.03209 (2018) - [i8]Shinichi Shirakawa, Youhei Akimoto, Kazuki Ouchi, Kouzou Ohara:
Sample Reuse via Importance Sampling in Information Geometric Optimization. CoRR abs/1805.12388 (2018) - [i7]Kouhei Nishida, Hernán E. Aguirre, Shota Saito, Shinichi Shirakawa, Youhei Akimoto:
Parameterless Stochastic Natural Gradient Method for Discrete Optimization and its Application to Hyper-Parameter Optimization for Neural Network. CoRR abs/1809.06517 (2018) - [i6]Naoki Sakamoto, Youhei Akimoto:
Ranking Based Linear Constraint Handling Method with Adaptive Penalty. CoRR abs/1811.00764 (2018) - 2017
- [j4]Osamu Takyu, Shohei Fujii, Youhei Akimoto, Mai Ohta, Takeo Fujii, Fumihito Sasamori, Shiro Handa:
Optimal cluster head selection and rotation of cognitive wireless sensor networks for simultaneous data gathering and long life system. Int. J. Distributed Sens. Networks 13(12) (2017) - [c29]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Quality Gain Analysis of the Weighted Recombination Evolution Strategy on General Convex Quadratic Functions. FOGA 2017: 111-126 - [c28]Naoki Sakamoto, Youhei Akimoto:
Modified box constraint handling for the covariance matrix adaptation evolution strategy. GECCO (Companion) 2017: 183-184 - [c27]Keigo Tanaka, Youhei Akimoto:
Introducing the cumulation to the population based incremental learning and the compact GA to relax genetic drift. GECCO (Companion) 2017: 199-200 - [c26]Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. GECCO (Companion) 2017: 641-674 - [c25]Hidekazu Miyazawa, Youhei Akimoto:
Effect of the mean vector learning rate in CMA-ES. GECCO 2017: 721-728 - [c24]Takahiro Yamaguchi, Youhei Akimoto:
Benchmarking the novel CMA-ES restart strategy using the search history on the BBOB noiseless testbed. GECCO (Companion) 2017: 1780-1787 - [i5]Youhei Akimoto:
Fast Eigen Decomposition for Low-Rank Matrix Approximation. CoRR abs/1706.02069 (2017) - 2016
- [c23]Youhei Akimoto, Nikolaus Hansen:
Projection-Based Restricted Covariance Matrix Adaptation for High Dimension. GECCO 2016: 197-204 - [c22]Kouhei Nishida, Youhei Akimoto:
Population Size Adaptation for the CMA-ES Based on the Estimation Accuracy of the Natural Gradient. GECCO 2016: 237-244 - [c21]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Introduction to Randomized Continuous Optimization. GECCO (Companion) 2016: 333-355 - [c20]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
CMA-ES and Advanced Adaptation Mechanisms. GECCO (Companion) 2016: 533-562 - [c19]Kouhei Nishida, Youhei Akimoto:
Evaluating the Population Size Adaptation Mechanism for CMA-ES on the BBOB Noiseless Testbed. GECCO (Companion) 2016: 1185-1192 - [c18]Kouhei Nishida, Youhei Akimoto:
Evaluating the Population Size Adaptation Mechanism for CMA-ES on the BBOB Noisy Testbed. GECCO (Companion) 2016: 1193-1200 - [c17]Youhei Akimoto, Nikolaus Hansen:
Online Model Selection for Restricted Covariance Matrix Adaptation. PPSN 2016: 3-13 - 2015
- [j3]