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ORCIDShinichi Shirakawa
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- affiliation: Yokohama National University, Kanagawa, Japan
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2020 – today
- 2024
[j9]Takuya Matsuda, Kento Uchida
, Shota Saito, Shinichi Shirakawa:
HACNet: End-to-end learning of interpretable table-to-image converter and convolutional neural network. Knowl. Based Syst. 284: 111293 (2024)- [j8]Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
Marginal Probability-Based Integer Handling for CMA-ES Tackling Single- and Multi-Objective Mixed-Integer Black-Box Optimization. ACM Trans. Evol. Learn. Optim. 4(2): 10 (2024) - [c55]Ryoki Hamano, Shota Saito, Masahiro Nomura, Kento Uchida, Shinichi Shirakawa:
CatCMA : Stochastic Optimization for Mixed-Category Problems. GECCO 2024 - [c54]Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa:
CMA-ES for Safe Optimization. GECCO 2024 - [c53]Kento Uchida, Kenta Nishihara, Shinichi Shirakawa:
CMA-ES with Adaptive Reevaluation for Multiplicative Noise. GECCO 2024 - [c52]Yutaro Yamada, Kento Uchida, Shinichi Shirakawa:
How to Make Multi-Objective Evolutionary Algorithms Invariant to Monotonically Increasing Transformation of Objective Functions. GECCO Companion 2024: 383-386 - [c51]Youhei Akimoto, Shinichi Shirakawa:
Analysis of Search Space Design for Neural Architecture Search with Weight Sharing. IJCNN 2024: 1-8 - [c50]Masashi Noguchi, Shinichi Shirakawa:
Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization. IJCNN 2024: 1-8 - [c49]Yasutoshi Kishimoto, Kota Yamanishi, Takuya Matsuda, Shinichi Shirakawa:
Neural Additive and Basis Models with Feature Selection and Interactions. PAKDD (3) 2024: 3-16 - [c48]Yuta Sekino, Kento Uchida, Shinichi Shirakawa:
Warm Starting of CMA-ES for Contextual Optimization Problems. PPSN (2) 2024: 205-220 - [c47]Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa:
CMA-ES for Discrete and Mixed-Variable Optimization on Sets of Points. PPSN (2) 2024: 236-251 - [c46]Ryoki Hamano, Shinichi Shirakawa, Masahiro Nomura:
Natural Gradient Interpretation of Rank-One Update in CMA-ES. PPSN (2) 2024: 252-267 - [i20]Ryoki Hamano, Shota Saito, Masahiro Nomura, Kento Uchida, Shinichi Shirakawa:
CatCMA : Stochastic Optimization for Mixed-Category Problems. CoRR abs/2405.09962 (2024) - [i19]Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa:
CMA-ES for Safe Optimization. CoRR abs/2405.10534 (2024) - [i18]Kento Uchida, Kenta Nishihara, Shinichi Shirakawa:
CMA-ES with Adaptive Reevaluation for Multiplicative Noise. CoRR abs/2405.11471 (2024) - [i17]Ryoki Hamano, Shinichi Shirakawa, Masahiro Nomura:
Natural Gradient Interpretation of Rank-One Update in CMA-ES. CoRR abs/2406.16506 (2024) - [i16]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) - [i15]Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa:
CMA-ES for Discrete and Mixed-Variable Optimization on Sets of Points. CoRR abs/2408.13046 (2024) - 2023
- [j7]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) - [c45]Yutaro Yamada, Kento Uchida, Shota Saito, Shinichi Shirakawa:
Surrogate-Assisted (1+1)-CMA-ES with Switching Mechanism of Utility Functions. EvoApplications@EvoStar 2023: 798-814 - [c44]Yohei Watanabe, Kento Uchida, Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
(1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems. GECCO 2023: 882-890 - [c43]Genki Sakata, Naoshi Kaneko, Dai Hasegawa, Shinichi Shirakawa:
Language Agnostic Gesture Generation Model: A Case Study of Japanese Speakers' Gesture Generation Using English Text-to-Gesture Model. VISIGRAPP (2: HUCAPP) 2023: 47-54 - [i14]Masashi Noguchi, Shinichi Shirakawa:
Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization. CoRR abs/2303.18031 (2023) - [i13]Yohei Watanabe, Kento Uchida, Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
(1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems. CoRR abs/2305.00849 (2023) - 2022
- [j6]Kento Uchida, Genki Sakata, Tetsushi Watari, Yuta Yamakita, Shinichi Shirakawa:
Generation of microscopic structure of solder material with desirable characteristics based on deep learning. Knowl. Based Syst. 258: 110017 (2022) - [j5]Eiichi Asakawa, Naoshi Kaneko, Dai Hasegawa, Shinichi Shirakawa:
Evaluation of text-to-gesture generation model using convolutional neural network. Neural Networks 151: 365-375 (2022) - [c42]Ryoki Hamano, Shinichi Shirakawa:
Reduction of genetic drift in population-based incremental learning via entropy regularization. GECCO Companion 2022: 491-494 - [c41]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 - [c40]Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
CMA-ES with margin: lower-bounding marginal probability for mixed-integer black-box optimization. GECCO 2022: 639-647 - [c39]Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
Benchmarking CMA-ES with margin on the bbob-mixint testbed. GECCO Companion 2022: 1708-1716 - [c38]Shoma Shimizu, Takayuki Nishio, Shota Saito, Yoichi Hirose, Yen-Hsiu Chen, Shinichi Shirakawa:
Neural Architecture Search for Improving Latency-Accuracy Trade-off in Split Computing. GLOBECOM (Workshops) 2022: 1864-1870 - [c37]Masayuki Kobayashi, Shinichi Shirakawa, Tomoharu Nagao:
Auxiliary Data Selection in Percolative Learning Method for Improving Neural Network Performance. ICAART (3) 2022: 381-387 - [c36]Yuhei Noda, Shota Saito, Shinichi Shirakawa:
Efficient Search of Multiple Neural Architectures with Different Complexities via Importance Sampling. ICANN (4) 2022: 607-619 - [c35]Teppei Yamaguchi, Kento Uchida, Shinichi Shirakawa:
Improvement of sep-CMA-ES for Optimization of High-Dimensional Functions with Low Effective Dimensionality. SSCI 2022: 1659-1668 - [i12]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) - [i11]Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization. CoRR abs/2205.13482 (2022) - [i10]Yuhei Noda, Shota Saito, Shinichi Shirakawa:
Efficient Search of Multiple Neural Architectures with Different Complexities via Importance Sampling. CoRR abs/2207.10334 (2022) - [i9]Shoma Shimizu, Takayuki Nishio, Shota Saito, Yoichi Hirose, Yen-Hsiu Chen, Shinichi Shirakawa:
Neural Architecture Search for Improving Latency-Accuracy Trade-off in Split Computing. CoRR abs/2208.13968 (2022) - [i8]Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
CMA-ES with Margin for Single-and Multi-Objective Mixed-Integer Black-Box Optimization. CoRR abs/2212.09260 (2022) - 2021
- [c34]Yoichi Hirose, Nozomu Yoshinari, Shinichi Shirakawa:
NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters. ACML 2021: 1349-1364 - [c33]Satoshi Arai, Shinichi Shirakawa, Tomoharu Nagao:
Non-strict Attentional Region Annotation to Improve Image Classification Accuracy. SMC 2021: 2375-2380 - [i7]Yoichi Hirose, Nozomu Yoshinari, Shinichi Shirakawa:
NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters. CoRR abs/2110.10165 (2021) - 2020
- [j4]Masanori Suganuma, Masayuki Kobayashi, Shinichi Shirakawa, Tomoharu Nagao:
Evolution of Deep Convolutional Neural Networks Using Cartesian Genetic Programming. Evol. Comput. 28(1): 141-163 (2020) - [j3]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) - [c32]Wataru Shibayama, Shinichi Shirakawa:
Reinforcement Learning-Based Redirection Controller for Efficient Redirected Walking in Virtual Maze Environment. CGI 2020: 33-45 - [c31]Teppei Yamaguchi, Kento Uchida, Shinichi Shirakawa:
Adaptive Stochastic Natural Gradient Method for Optimizing Functions with Low Effective Dimensionality. PPSN (1) 2020: 719-731 - [p1]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming. Deep Neural Evolution 2020: 185-208
2010 – 2019
- 2019
- [c30]Shota Saito, Shinichi Shirakawa:
Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures. ICANN (2) 2019: 393-405 - [c29]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 - [c28]Kento Uchida, Shota Saito, Panca Dewi Pamungkasari, Yusei Kawai, Ita Fauzia Hanoum, Filbert H. Juwono, Shinichi Shirakawa:
Joint Optimization of Convolutional Neural Network and Image Preprocessing Selection for Embryo Grade Prediction in In Vitro Fertilization. ISVC (2) 2019: 14-24 - [c27]Ryotaro Abe, Taichi Takeda, Ryo Shiratori, Shinichi Shirakawa, Shota Saito, Toshihiko Baba:
Optimization of H0 Photonic Crystal Nanocavity using Neural Network. OECC/PSC 2019: 1-3 - [i6]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) - [i5]Shota Saito, Shinichi Shirakawa:
Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures. CoRR abs/1907.06341 (2019) - 2018
- [c26]Shinichi Shirakawa, Yasushi Iwata, Youhei Akimoto:
Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling. AAAI 2018: 4074-4082 - [c25]Kento Uchida, Shinichi Shirakawa, Youhei Akimoto:
Analysis of information geometric optimization with isotropic gaussian distribution under finite samples. GECCO 2018: 897-904 - [c24]Shota Saito, Shinichi Shirakawa, Youhei Akimoto:
Embedded feature selection using probabilistic model-based optimization. GECCO (Companion) 2018: 1922-1925 - [c23]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. IJCAI 2018: 5369-5373 - [c22]Dai Hasegawa, Naoshi Kaneko, Shinichi Shirakawa, Hiroshi Sakuta, Kazuhiko Sumi:
Evaluation of Speech-to-Gesture Generation Using Bi-Directional LSTM Network. IVA 2018: 79-86 - [i4]Shinichi Shirakawa, Yasushi Iwata, Youhei Akimoto:
Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling. CoRR abs/1801.07650 (2018) - [i3]Shinichi Shirakawa, Youhei Akimoto, Kazuki Ouchi, Kouzou Ohara:
Sample Reuse via Importance Sampling in Information Geometric Optimization. CoRR abs/1805.12388 (2018) - [i2]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) - 2017
- [c21]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
A genetic programming approach to designing convolutional neural network architectures. GECCO 2017: 497-504 - [c20]Kenta Takeuchi, Dai Hasegawa, Shinichi Shirakawa, Naoshi Kaneko, Hiroshi Sakuta, Kazuhiko Sumi:
Speech-to-Gesture Generation: A Challenge in Deep Learning Approach with Bi-Directional LSTM. HAI 2017: 365-369 - [i1]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. CoRR abs/1704.00764 (2017) - 2016
- [j2]Shinichi Shirakawa, Tomoharu Nagao:
Bag of local landscape features for fitness landscape analysis. Soft Comput. 20(10): 3787-3802 (2016) - [c19]Shinichi Shirakawa:
Impact of invariant objective for order preserving transformation in Bayesian optimization. CEC 2016: 1432-1437 - [c18]Masanori Suganuma, Daiki Tsuchiya, Shinichi Shirakawa, Tomoharu Nagao:
Hierarchical feature construction for image classification using Genetic Programming. SMC 2016: 1423-1428 - 2015
- [j1]Shinichi Shirakawa:
Multiple Binary Codes for Fast Approximate Similarity Search. IEICE Trans. Inf. Syst. 98-D(3): 671-680 (2015) - [c17]Shinichi Shirakawa, Youhei Akimoto, Kazuki Ouchi, Kouzou Ohara:
Sample Reuse in the Covariance Matrix Adaptation Evolution Strategy Based on Importance Sampling. GECCO 2015: 305-312 - [c16]Dai Hasegawa, Shinichi Shirakawa, Naoya Shioiri, Toshiki Hanawa, Hiroshi Sakuta, Kouzou Ohara:
The Effect of Metaphoric Gestures on Schematic Understanding of Instruction Performed by a Pedagogical Conversational Agent. HCI (24) 2015: 361-371 - [c15]Yu Kobayashi, Dai Hasegawa, Shinichi Shirakawa, Hiroshi Sakuta, Eijun Nakayama:
Development of Web-Based Platform for Privacy Protective Avatar Mediated Distance-Care. MindCare 2015: 131-139 - 2014
- [c14]Shinichi Shirakawa:
Fast Similarity Search Using Multiple Binary Codes. ICPR 2014: 3714-3719 - [c13]Youhei Akimoto, Shinichi Shirakawa:
Natural Gradient Approach for Linearly Constrained Continuous Optimization. PPSN 2014: 252-261 - [c12]Shinichi Shirakawa, Tomoharu Nagao:
Local Landscape Patterns for Fitness Landscape Analysis. SEAL 2014: 467-478 - 2010
- [c11]Yuta Nakano, Shinichi Shirakawa, Noriko Yata, Tomoharu Nagao:
Automatic construction of image transformation algorithms using feature based genetic image network. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c10]Shinichi Shirakawa, Noriko Yata, Tomoharu Nagao:
Evolving search spaces to emphasize the performance difference of real-coded crossovers using genetic programming. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c9]Shiro Nakayama, Shinichi Shirakawa, Noriko Yata, Tomoharu Nagao:
Ensemble Image Classification Method Based on Genetic Image Network. EuroGP 2010: 313-324
2000 – 2009
- 2009
- [c8]Shinichi Shirakawa, Tomoharu Nagao:
Evolutionary image segmentation based on multiobjective clustering. IEEE Congress on Evolutionary Computation 2009: 2466-2473 - [c7]Shinichi Shirakawa, Tomoharu Nagao:
Evolution of Search Algorithms Using Graph Structured Program Evolution. EuroGP 2009: 109-120 - [c6]Shinichi Shirakawa, Shiro Nakayama, Tomoharu Nagao:
Genetic Image Network for Image Classification. EvoWorkshops 2009: 395-404 - [c5]Shinichi Shirakawa, Tomoharu Nagao:
Graph structured program evolution with automatically defined nodes. GECCO 2009: 1107-1114 - 2008
- [c4]Shinichi Shirakawa, Tomoharu Nagao:
Evolutionary algorithm considering program size: efficient program evolution using grape. GECCO (Companion) 2008: 2217-2222 - 2007
- [c3]Shinichi Shirakawa, Shintaro Ogino, Tomoharu Nagao:
Graph structured program evolution. GECCO 2007: 1686-1693 - [c2]Shinichi Shirakawa, Tomoharu Nagao:
Feed Forward Genetic Image Network: Toward Efficient Automatic Construction of Image Processing Algorithm. ISVC (2) 2007: 287-297 - [c1]Shinichi Shirakawa, Tomoharu Nagao:
Evolution of sorting algorithm using graph structured program evolution. SMC 2007: 1256-1261
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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