Publications

Last Update: October 31, 2024

Journal Papers

  1. Ryoki Hamano, Kento Uchida, Shinichi Shirakawa, Daiki Morinaga, and Youhei Akimoto: Tail Bounds on the Runtime of Categorical Compact Genetic Algorithm, Evolutionary Computation (Accepted) [DOI] [arXiv]
  2. Ryoki Hamano, Shota Saito, Masahiro Nomura, and Shinichi Shirakawa: Marginal Probability-Based Integer Handling for CMA-ES Tackling Single-and Multi-Objective Mixed-Integer Black-Box Optimization, ACM Transactions on Evolutionary Learning and Optimization, Vol. 4, Issue.2, Article No.: 10, Jun. 2024. [DOI] [arXiv]
  3. Takuya Matsuda, Kento Uchida, Shota Saito, and Shinichi Shirakawa: HACNet: End-to-end learning of interpretable table-to-image converter and convolutional neural network, Knowledge-Based Systems, Vol. 284, 111293, Jan. 2024. [DOI]
  4. Kotaro Sakamoto, Hideaki Ishibashi, Rei Sato, Shinichi Shirakawa, Youhei Akimoto, and Hideitsu Hino: ATNAS: Automatic Termination for Neural Architecture Search, Neural Networks, Vol. 166, pp. 446-458, Sep. 2023. [DOI]
  5. Kento Uchida, Genki Sakata, Tetsushi Watari, Yuta Yamakita, and Shinichi Shirakawa: Generation of microscopic structure of solder material with desirable characteristics based on deep learning, Knowledge-Based Systems, Vol. 258, 110017, Dec. 2022. [DOI]
  6. Shoma Shimizu, Kenta Nishihara, Yoshiki Miyauchi, Kouki Wakita, Rin Suyama, Atsuo Maki, and Shinichi Shirakawa: Automatic berthing using supervised learning and reinforcement learning, Ocean Engineering, Vol. 265, 112553, Dec. 2022. [DOI]
  7. Eiichi Asakawa, Naoshi Kaneko, Dai Hasegawa, and Shinichi Shirakawa: Evaluation of text-to-gesture generation model using convolutional neural network, Neural Networks, Vol. 151, pp. 365-375, Jul. 2022. [DOI] [Demo Video] [Code]
  8. Minami Masumoto, Ittetsu Fukuda, Suguru Furihata, Takahiro Arai, Tatsuto Kageyama, Kiyomi Ohmori, Shinichi Shirakawa, and Junji Fukuda: Deep neural network for the determination of transformed foci in Bhas 42 cell transformation assay, Scientific Reports, volume 11, Article number: 23344, Dec. 2021. [DOI]
  9. Kento Uchida, Shinichi Shirakawa, and Youhei Akimoto: Finite-Sample Analysis of Information Geometric Optimization with Isotropic Gaussian Distribution on Convex Quadratic Functions, IEEE Transactions on Evolutionary Computation, Vol. 24, Issue 6, pp. 1035-1049, Dec. 2020. [DOI]
  10. Masanori Suganuma, Masayuki Kobayashi, Shinichi Shirakawa, and Tomoharu Nagao: Evolution of Deep Convolutional Neural Networks Using Cartesian Genetic Programming, Evolutionary Computation, Vol. 28, Issue 1, pp. 141-163, Mar. 2020. [DOI]
  11. Ryotaro Abe, Taichi Takeda, Ryo Shiratori, Shinichi Shirakawa, Shota Saito, and Toshihiko Baba: Optimization of an H0 photonic crystal nanocavity using machine learning, Optics Letters, Vol. 45, Issue 2, pp. 319-322, Jan. 2020. [DOI]
  12. Shinichi Shirakawa and Tomoharu Nagao: Bag of local landscape features for fitness landscape analysis, Soft Computing, Vol. 20, Issue 10, pp. 3787-3802, Feb. 2016. [DOI] [ReadCube]
  13. Shinichi Shirakawa: Multiple Binary Codes for Fast Approximate Similarity Search, IEICE Transactions on Information and Systems, Vol. E98-D, No. 3, pp. 671-680, Mar. 2015. [DOI] [IEICE site]
  14. Shinichi Shirakawa, Shintaro Ogino, and Tomoharu Nagao: Dynamic Ant Programming for Automatic Construction of Programs, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol. 3, Issue 5, pp. 540-548, Sep. 2008. [DOI]
  15. Shinichi Shirakawa and Tomoharu Nagao: Action Control of Autonomous Agents in Continuous Valued Space Using RFCN, Electronics and Communications in Japan, Vol. 91, Issue 2, pp. 31-39, Sep. 2008. [DOI]

Conference Papers

  1. Chen Yen-Hsiu, Yoichi Hirose, Shoma Shimizu, Shota Saito, Kento Uchida, Shinichi Shirakawa, and Takayuki Nishio: Enhancing Latency-Accuracy Tradeoff in Dynamic Split Inference via Vector Quantized Bottleneck, 2024 IEEE Globecom Workshops, Ubiquitous Network Intelligence for Next Generation Wireless Networks, Cape Town, South Africa, December 8-12, 2024.
  2. Shoma Shimizu, Kento Uchida, Atsuo Maki, and Shinichi Shirakawa: Adaptive Trust Region Radius for Robust Policy Optimization, 31st International Conference on Neural Information Processing (ICONIP 2024), Auckland, New Zealand December 2-6, 2024 (Accepted)
  3. Satoshi Arai, Shinichi Shirakawa, and Tomoharu Nagao: BINN-DT: Towards Better Interpretability of Multidimensional Decision Rules via Bivariate Nonlinear Node Decision Trees, 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Sarawak, Malaysia, October 6-10, 2024. (Accepted)
  4. Yuta Sekino, Kento Uchida, and Shinichi Shirakawa: Warm Starting of CMA-ES for Contextual Optimization Problems, Proceedings of the 18th International Conference on Parallel Problem Solving from Nature (PPSN 2024), Part II, Vol. 15149 of LNCS, pp. 205-220, Hagenberg, Austria, September 14-18, 2024. [DOI]
  5. Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, and Shinichi Shirakawa: CMA-ES for Discrete and Mixed-Variable Optimization on Sets of Points, Proceedings of the 18th International Conference on Parallel Problem Solving from Nature (PPSN 2024), Part II, Vol. 15149 of LNCS, pp. 236-251, Hagenberg, Austria, September 14-18, 2024. [DOI] [arXiv]
  6. Ryoki Hamano, Shinichi Shirakawa, and Masahiro Nomura: Natural Gradient Interpretation of Rank-One Update in CMA-ES, Proceedings of the 18th International Conference on Parallel Problem Solving from Nature (PPSN 2024), Part II, Vol. 15149 of LNCS, pp. 252–267, Hagenberg, Austria, September 14-18, 2024. [DOI] [arXiv] [Code]
  7. Yoichi Hirose, Kento Uchida, and Shinichi Shirakawa: Fine-Tuning LLMs for Automated Feature Engineering, International Conference on Automated Machine Learning (AutoML Conference) 2024 Workshop Track, Paris, France, September 9-12, 2024. [Link]
  8. Kento Uchida, Kenta Nishihara, and Shinichi Shirakawa: CMA-ES with Adaptive Reevaluation for Multiplicative Noise, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2024), pp. 731-739, Melbourne, Australia (hybrid), July 14-18, 2024. [DOI] [arXiv] [Code]
  9. Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, and Shinichi Shirakawa: CMA-ES for Safe Optimization, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2024), pp. 722-730, Melbourne, Australia (hybrid), July 14-18, 2024. [DOI] [arXiv]
  10. Ryoki Hamano, Shota Saito, Masahiro Nomura, Kento Uchida, and Shinichi Shirakawa: CatCMA : Stochastic Optimization for Mixed-Category Problems, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2024), pp. 656-664, Melbourne, Australia (hybrid), July 14-18, 2024. [DOI] [arXiv] [Code]
  11. Yutaro Yamada, Kento Uchida, and Shinichi Shirakawa: How to Make Multi-Objective Evolutionary Algorithms Invariant to Monotonically Increasing Transformation of Objective Functions, Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2024, Poster Paper), pp. 383-386, Melbourne, Australia (hybrid), July 14-18, 2024. [DOI]
  12. Youhei Akimoto and Shinichi Shirakawa: Analysis of Search Space Design for Neural Architecture Search with Weight Sharing, 2024 International Joint Conference on Neural Networks (IJCNN 2024) (IEEE World Congress on Computational Intelligence (WCCI 2024)), Yokohama, Japan, June 30 - July 5, 2024. [DOI]
  13. Masashi Noguchi and Shinichi Shirakawa: Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization, 2024 International Joint Conference on Neural Networks (IJCNN 2024) (IEEE World Congress on Computational Intelligence (WCCI 2024)), Yokohama, Japan, June 30 - July 5, 2024. [DOI] [arXiv] [Code]
  14. Yasutoshi Kishimoto, Kota Yamanishi, Takuya Matsuda, and Shinichi Shirakawa: Neural Additive and Basis Models with Feature Selection and Interactions, Proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2024), Part III, Vol. 14647 of LNAI, pp. 3-16, Taipei, Taiwan, May 7–10, 2024. [DOI]
  15. Yohei Watanabe, Kento Uchida, Ryoki Hamano, Shota Saito, Masahiro Nomura, and Shinichi Shirakawa: (1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2023), pp. 882-890, Lisbon, Portugal (hybrid), July 15-19, 2023. [DOI] [arXiv] [Code]
  16. Yutaro Yamada, Kento Uchida, Shota Saito, and Shinichi Shirakawa: Surrogate-Assisted (1+1)-CMA-ES with Switching Mechanism of Utility Functions, Applications of Evolutionary Computation (EvoApplications 2023, Part of EvoStar 2023), Vol. 13989 of LNCS, pp. 798-814, Brno, Czech Republic, April 12-14, 2023. [DOI]
  17. Genki Sakata, Naoshi Kaneko, Dai Hasegawa, and Shinichi Shirakawa: Language Agnostic Gesture Generation Model: A Case Study of Japanese Speakers’ Gesture Generation Using English Text-to-Gesture Model, Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - HUCAPP, pp. 47-54, Lisbon, Portugal, February 19-21, 2023. [DOI]
  18. Shoma Shimizu, Takayuki Nishio, Shota Saito, Yoichi Hirose, Chen Yen-Hsiu, and Shinichi Shirakawa: Neural Architecture Search for Improving Latency-Accuracy Trade-off in Split Computing, 2022 IEEE Globecom Workshops, Edge Learning over 5G Mobile Networks and Beyond, pp. 1864-1870, Rio de Janeiro, Brazil, December 4-8, 2022. [DOI] [arXiv]
  19. Teppei Yamaguchi, Kento Uchida, and Shinichi Shirakawa: Improvement of sep-CMA-ES for Optimization of High-Dimensional Functions with Low Effective Dimensionality, 2022 IEEE Symposium Series On Computational Intelligence (SSCI), pp. 1659-1668, Singapore, December 4-7, 2022. [DOI] [Code]
  20. Yuhei Noda, Shota Saito, and Shinichi Shirakawa: Efficient Search of Multiple Neural Architectures with Different Complexities via Importance Sampling, Proceedings of the 31st International Conference on Artificial Neural Networks (ICANN 2022), Part IV, Vol. 13532 of LNCS, pp. 607–619, Bristol, United Kingdom, September 6-9 2022. [DOI] [arXiv]
  21. Ryoji Tanabe, Youhei Akimoto, Ken Kobayashi, Hiroshi Umeki, Shinichi Shirakawa, and Naoki Hamada: A Two-phase Framework with a Bezier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2022), pp. 601-610, Boston, MA, USA (hybrid), July 9-13, 2022. [DOI] [arXiv]
  22. Ryoki Hamano, Shota Saito, Masahiro Nomura, and Shinichi Shirakawa: CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2022), pp. 639-647, Boston, MA, USA (hybrid), July 9-13, 2022 (Best Paper Nomination). [DOI] [arXiv] [Code]
  23. Ryoki Hamano and Shinichi Shirakawa: Reduction of Genetic Drift in Population-Based Incremental Learning via Entropy Regularization, Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2022, Poster Paper), pp. 491–494, Boston, MA, USA (hybrid), July 9-13, 2022. [DOI]
  24. Ryoki Hamano, Shota Saito, Masahiro Nomura, and Shinichi Shirakawa: Benchmarking CMA-ES with Margin on the bbob-mixint Testbed, Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO Workshop on Black-Box Optimization Benchmarking (BBOB 2022)), pp. 1708–1716, Boston, MA, USA (hybrid), July 9-13, 2022. [DOI]
  25. Masayuki Kobayashi, Shinichi Shirakawa, and Tomoharu Nagao: Auxiliary Data Selection in Percolative Learning Method for Improving Neural Network Performance, Proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART), Vol. 3, pp. 381-387, Online Streaming, February 3-5, 2022. [DOI]
  26. Yoichi Hirose, Nozomu Yoshinari, and Shinichi Shirakawa: NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters, Proceedings of the 13th Asian Conference on Machine Learning (ACML 2021), Vol. 157 of PMLR, pp. 1349-1364, Virtual Conference, November 17-19, 2021. [Link] [arXiv] [Dataset API]
  27. Satoshi Arai, Shinichi Shirakawa, and Tomoharu Nagao: Non-strict Attentional Region Annotation to Improve Image Classification Accuracy, Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021), pp. 2375-2380, Melbourne, Australia (Virtual), October 17-20, 2021. [DOI] [Dataset]
  28. Wataru Shibayama and Shinichi Shirakawa: Reinforcement Learning-Based Redirection Controller for Efficient Redirected Walking in Virtual Maze Environment, Proceedings of the 37th Computer Graphics International Conference (CGI 2020), Vol. 12221 of LNCS, pp. 33-45, Geneva, Switzerland (Virtual), October 20-23, 2020. [DOI] [PDF]
  29. Teppei Yamaguchi, Kento Uchida, and Shinichi Shirakawa: Adaptive Stochastic Natural Gradient Method for Optimizing Functions with Low Effective Dimensionality, Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI), Part I, Vol. 12269 of LNCS, pp. 719-731, Leiden, The Netherlands, September 5-9, 2020. [DOI] [PDF]
  30. Kento Uchida, Shota Saito, Panca Dewi Pamungkasari, Yusei Kawai, Ita Fauzia Hanoum, Filbert Hilman Juwono, and Shinichi Shirakawa: Joint Optimization of Convolutional Neural Network and Image Preprocessing Selection for Embryo Grade Prediction in In Vitro Fertilization, Proceedings of the 14th International Symposium on Visual Computing (ISVC 2019), Part II, Vol. 11845 of LNCS, pp. 14–24, Lake Tahoe, Nevada, USA, October 7-9, 2019. [DOI] [PDF]
  31. Shota Saito and Shinichi Shirakawa: Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures, Proceedings of the 28th International Conference on Artificial Neural Networks (ICANN 2019), Part II, Vol. 11728 of LNCS, pp. 393–405, Munich, Germany, September 17-19, 2019. (Oral Presentation) [DOI] [arXiv]
  32. Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari, Kento Uchida, Shota Saito, and Kouhei Nishida: Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search, Proceedings of the 36th International Conference on Machine Learning (ICML 2019), Vol. 97 of PMLR, pp. 171-180, Long Beach, California, USA, June 9-15, 2019. [Link] [arXiv] [Code]
  33. Dai Hasegawa, Naoshi Kaneko, Shinichi Shirakawa, Hiroshi Sakuta, and Kazuhiko Sumi: Evaluation of Speech-to-Gesture Generation Using Bi-Directional LSTM Network, Proceedings of the 18th International Conference on Intelligent Virtual Agents (IVA ‘18), pp. 79-86, Sydney, NSW, Australia, November 5-8, 2018. [DOI]
  34. Kento Uchida, Shinichi Shirakawa, and Youhei Akimoto: Analysis of Information Geometric Optimization with Isotropic Gaussian Distribution Under Finite Samples, Proceedings of the Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), pp. 897-904, Kyoto, Japan, July 15-19, 2018. [DOI] [PDF]
  35. Shota Saito, Shinichi Shirakawa, and Youhei Akimoto: Embedded Feature Selection Using Probabilistic Model-Based Optimization, Proceedings of the Genetic and Evolutionary Computation Conference Companion (Student workshop at GECCO 2018), pp. 1922-1925, Kyoto, Japan, July 15-19, 2018. [DOI] [PDF]
  36. Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao: A Genetic Programming Approach to Designing Convolutional Neural Network Architectures, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), Sister Conferences Best Papers Track, pp. 5369-5373, Stockholm, Sweden, July 13-19, 2018. [DOI]
  37. Shinichi Shirakawa, Yasushi Iwata, and Youhei Akimoto: Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling, Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), pp. 4074-4082, New Orleans, Louisiana, USA, February 2-7, 2018. [DOI] [arXiv]
  38. Kenta Takeuchi, Dai Hasegawa, Shinichi Shirakawa, Naoshi Kaneko, Hiroshi Sakuta, and Kazuhiko Sumi: Speech-to-Gesture Generation: A Challenge in Deep Learning Approach with Bi-Directional LSTM, Proceedings of the 5th International Conference on Human-Agent Interaction (HAI 2017), Poster and Late-breaking, pp. 365-369, Bielefeld, Germany, October 17-20, 2017. [DOI]
  39. Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao: A Genetic Programming Approach to Designing Convolutional Neural Network Architectures, Proceedings of the Genetic and Evolutionary Computation Conference 2017 (GECCO 2017), pp. 497-504, Berlin, Germany, July 15-19, 2017. (Best Paper Award) [DOI] [arXiv] [Code]
  40. Masanori Suganuma, Daiki Tsuchiya, Shinichi Shirakawa, and Tomoharu Nagao: Hierarchical Feature Construction for Image Classification Using Genetic Programming, Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016), pp. 1423-1428, Budapest, Hungary, October 9-12, 2016. [DOI] [PDF]
  41. Shinichi Shirakawa: Impact of Invariant Objective for Order Preserving Transformation in Bayesian Optimization, Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC 2016) (2016 IEEE World Congress on Computational Intelligence (WCCI 2016)), pp. 1432-1437, Vancouver, Canada, July 24-29, 2016. [DOI] [PDF]
  42. Dai Hasegawa, Shinichi Shirakawa, Naoya Shioiri, Toshiki Hanawa, Hiroshi Sakuta, and Kouzou Ohara: The Effect of Metaphoric Gestures on Schematic Understanding of Instruction Performed by a Pedagogical Conversational Agent, Proceedings of the 2nd International Conference on Learning and Collaboration Technologies (LCT 2015), Held as Part of HCI International 2015, Vol. 9192 of LNCS, pp. 361-371, Los Angeles, CA, USA, August 2-7, 2015. [DOI]
  43. Yu Kobayashi, Dai Hasegawa, Shinichi Shirakawa, Hiroshi Sakuta, and Eijun Nakayama: Development of Web-based Platform for Privacy Protective Avatar Mediated Distance-Care, Proceedings of the 5th EAI International Symposium on Pervasive Computing Paradigms for Mental Health (MindCare 2015), Vol. 604 of the series Communications in Computer and Information Science, pp. 131-139, Milan, Italy, July 24-25, 2015. [DOI]
  44. Shinichi Shirakawa, Youhei Akimoto, Kazuki Ouchi, and Kouzou Ohara: Sample Reuse in the Covariance Matrix Adaptation Evolution Strategy Based on Importance Sampling, Proceedings of the Genetic and Evolutionary Computation Conference 2015 (GECCO 2015), pp. 305-312, Madrid, Spain, July 11-15, 2015. [DOI] [PDF]
  45. Shinichi Shirakawa and Tomoharu Nagao: Local Landscape Patterns for Fitness Landscape Analysis, Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014), Vol. 8886 of LNCS, pp. 467-478, Dunedin, New Zealand, December 15-18, 2014. [DOI] [PDF]
  46. Youhei Akimoto and Shinichi Shirakawa: Natural Gradient Approach for Linearly Constrained Continuous Optimization, Proceedings of the 13th International Conference on Parallel Problem Solving from Nature (PPSN XIII), Vol. 8672 of LNCS, pp. 252-261, Ljubljana, Slovenia, September 13-17, 2014. [DOI]
  47. Shinichi Shirakawa: Fast Similarity Search Using Multiple Binary Codes, Proceedings of the 22nd International Conference on Pattern Recognition (ICPR), pp. 3714-3719, Stockholm, Sweden, August 24-28, 2014. [DOI]
  48. Yasuaki Horima, Shinichi Shirakawa, Noriko Yata, and Tomoharu Nagao: Construction of Players’ Action for Robocup Soccer Using Graph Structured Program Evolution, Proceedings of SICE Annual Conference 2010, pp. 690-695, Taipei, Taiwan, August 18-21, 2010. [IEEE Xplore] [PDF]
  49. Yuta Nakano, Shinichi Shirakawa, Noriko Yata, and Tomoharu Nagao: Automatic Construction of Image Transformation Algorithms Using Feature Based Genetic Image Network, Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC 2010) (2010 IEEE World Congress on Computational Intelligence (WCCI 2010)), pp. 1232-1239, Barcelona, Spain, July 18-23, 2010. [DOI] [PDF]
  50. Shinichi Shirakawa, Noriko Yata, and Tomoharu Nagao: Evolving Search Spaces to Emphasize the Performance Difference of Real-Coded Crossovers Using Genetic Programming, Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC 2010) (2010 IEEE World Congress on Computational Intelligence (WCCI 2010)), pp. 2444-2451, Barcelona, Spain, July 18-23, 2010. [DOI] [PDF]
  51. Shiro Nakayama, Shinichi Shirakawa, Noriko Yata, and Tomoharu Nagao: Ensemble Image Classification Method Based on Genetic Image Network, Genetic Programming: Proceedings of the 13th European Conference on Genetic Programming (EuroGP 2010), Vol. 6021 of LNCS, pp. 313-324, Istanbul, Turkey, April 7-9, 2010. [DOI] [PDF]
  52. Shinichi Shirakawa and Tomoharu Nagao: Graph Structured Program Evolution with Automatically Defined Nodes, Proceedings of the Genetic and Evolutionary Computation Conference 2009 (GECCO 2009), pp. 1107-1114, Montreal, Canada, July 8-12, 2009. [DOI] [PDF]
  53. Shinichi Shirakawa and Tomoharu Nagao: Evolutionary Image Segmentation Based on Multiobjective Clustering, Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC 2009), pp. 2466-2473, Trondheim, Norway, May 18-21, 2009. [DOI] [PDF] [Code]
  54. Shinichi Shirakawa and Tomoharu Nagao: Evolution of Search Algorithms Using Graph Structured Program Evolution, Genetic Programming: Proceedings of the 12th European Conference on Genetic Programming (EuroGP 2009), Vol. 5481 of LNCS, pp. 109-120, Tübingen, Germany, April 15-17, 2009. [DOI] [PDF]
  55. Shinichi Shirakawa, Shiro Nakayama, and Tomoharu Nagao: Genetic Image Network for Image Classification, Applications of Evolutionary Computing: 11th European Workshop on Evolutionary Computation in Image Analysis and Signal Processing (EvoIASP 2009), Vol. 5484 of LNCS, pp. 395-404, Tübingen, Germany, April 15-17, 2009. [DOI] [PDF]
  56. Shinichi Shirakawa and Tomoharu Nagao: Evolutionary Algorithm Considering Program Size: Efficient Program Evolution using GRAPE, Proceedings of the Genetic and Evolutionary Computation Conference 2008 (GECCO 2008), Late-Breaking Papers, pp. 2217-2222, Atlanta, GA, USA, July 11-16, 2008. [DOI] [PDF]
  57. Shinichi Shirakawa and Tomoharu Nagao: Feed Forward Genetic Image Network: Toward Efficient Automatic Construction of Image Processing Algorithm, Advances in Visual Computing: Proceedings of the 3rd International Symposium on Visual Computing (ISVC 2007) Part II, Vol. 4842 of LNCS, pp. 287-297, Lake Tahoe, Nevada, USA, November 26-28 2007. [DOI] [PDF]
  58. Shinichi Shirakawa and Tomoharu Nagao: Evolution of Sorting Algorithm using Graph Structured Program Evolution, Proceedings of the 2007 IEEE International Conference on Systems, Man and Cybernetics (SMC 2007), pp. 1256-1261, Montreal, Canada, October 7-10, 2007. [DOI] [PDF]
  59. Shinichi Shirakawa, Shintaro Ogino, and Tomoharu Nagao: Graph Structured Program Evolution, Proceedings of the Genetic and Evolutionary Computation Conference 2007 (GECCO 2007), Vol. 2, pp. 1686-1693, London, England, July 7-11, 2007. [DOI] [PDF]
  60. Shinichi Shirakawa and Tomoharu Nagao: Genetic Image Network (GIN): Automatically Construction of Image Processing Algorithm, Proceedings of the International Workshop on Advanced Image Technology 2007 (IWAIT 2007), P3-34, pp. 643-648, Bangkok, Thailand, January 8-9, 2007. [PDF]

Conference Presentations

  1. Yuta Suzuki, Yukuto Yasuhiko, Shigeru Yamada, Yasunari Kanda, Keisuke Shima, Junji Fukuda, and Shinichi Shirakawa: Application of machine learning to neurotoxicity assessment using human iPS cell-derived neurons, International Neurotoxicology Association Conference (INA-18), Durham, NC, USA, May 21-25, 2023.
  2. Shota Saito and Shinichi Shirakawa: Introducing a Penalty Term to Control Structure Complexity in Dynamic Optimization of Neural Network Structures, 2018 JPNSEC International Workshop on Evolutionary Computation, pp. 45-48, Shenzhen, China, August 31 - September 1, 2018.
  3. Yusei Kawai and Shinichi Shirakawa: Dynamic Selection of Image Processing Filters for Convolutional Neural Networks, 2018 JPNSEC International Workshop on Evolutionary Computation, pp. 56-59, Shenzhen, China, August 31 - September 1, 2018.
  4. Kento Uchida, Youhei Akimoto, and Shinichi Shirakawa: Analysis of Information Geometric Optimization with Isotropic Gaussian Distribution: Toward Finite-Sample Analysis on Convex Quadratic Functions, 2018 JPNSEC International Workshop on Evolutionary Computation, pp. 102-106, Shenzhen, China, August 31 - September 1, 2018.
  5. Hirokazu Kobayashi, Shota Saito, and Shinichi Shirakawa: Dynamic Feature Construction for Neural Networks Using Probabilistic Model-Based Genetic Programming, 2018 JPNSEC International Workshop on Evolutionary Computation, pp. 113-117, Shenzhen, China, August 31 - September 1, 2018.

Book Chapters

  1. Panca Dewi Pamungkasari, Kento Uchida, Shota Saito, Filbert H. Juwono, Ita Fauzia Hanoum, and Shinichi Shirakawa: Embryo Grade Prediction for In-Vitro Fertilization, In U. Kose, O. Deperlioglu, D. J. Hemanth (eds), Deep Learning for Biomedical Applications, chapter 2, pp. 21-40, CRC Press, July 2021. [DOI]
  2. Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao: Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming, In H. Iba and N. Noman (eds), Deep Neural Evolution –Deep Learning with Evolutionary Computation, chapter 7, pp. 185-208, Springer, May 2020. [DOI]
  3. Shinichi Shirakawa, Shintaro Ogino, and Tomoharu Nagao: Automatic Construction of Programs Using Dynamic Ant Programming, Ant Colony Optimization - Methods and Applications, edited by Avi Ostfeld, chapter 6, pp. 75-88, IN-TECH, Feb. 2011. [DOI]
  4. Shinichi Shirakawa and Tomoharu Nagao: Graph Structured Program Evolution: Evolution of Loop Structures, In Rick L. Riolo and Una-May O’Reilly and Trent McConaghy editors, Genetic Programming Theory and Practice VII, chapter 11, pp. 177-194, Springer, Oct. 2009. [DOI]