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ORCIDTaku Hasegawa
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2020 – today
- 2023
[c17]Ryota Tanaka, Kyosuke Nishida, Kosuke Nishida, Taku Hasegawa, Itsumi Saito, Kuniko Saito:
SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images. AAAI 2023: 13636-13645- [c16]Taku Hasegawa, Kyosuke Nishida, Koki Maeda, Kuniko Saito:
DueT: Image-Text Contrastive Transfer Learning with Dual-adapter Tuning. EMNLP 2023: 13607-13624 - [i1]Ryota Tanaka, Kyosuke Nishida, Kosuke Nishida, Taku Hasegawa, Itsumi Saito, Kuniko Saito:
SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images. CoRR abs/2301.04883 (2023) - 2022
- [c15]Shumpei Miyawaki, Taku Hasegawa, Kyosuke Nishida, Takuma Kato, Jun Suzuki:
Scene-Text Aware Image and Text Retrieval with Dual-Encoder. ACL (student) 2022: 422-433 - 2021
- [j1]Takuya Fukushima, Tomoharu Nakashima
, Taku Hasegawa, Vicenç Torra:
Optimal Value Estimation of Intentional-Value-Substitution for Learning Regression Models. J. Adv. Comput. Intell. Intell. Informatics 25(2): 153-161 (2021)
2010 – 2019
- 2019
- [c14]Takuya Fukushima, Taku Hasegawa, Tomoharu Nakashima:
Estimating Optimal Values for Intentional-Value-Substitution Learning. MDAI 2019: 319-329 - 2018
- [c13]Ryo Iwasaki, Taku Hasegawa, Naoki Mori, Keinosuke Matsumoto:
Relaxation Method of Convolutional Neural Networks for Natural Language Processing. DCAI 2018: 188-195 - [c12]Taku Hasegawa, Tomoharu Nakashima:
A Study on a Parallelization of Parameter-Less Population Pyramid. SCIS&ISIS 2018: 261-266 - [c11]Taku Hasegawa, Naoki Mori, Keinosuke Matsumoto:
Genetic Programming with Multi-Layered Population Structure for Software Evolution. SoMeT 2018: 57-70 - 2017
- [c10]Naoki Mori, Taku Hasegawa, Kento Tsukada, Keinosuke Matsumoto:
Analysis of scaling for fitness landscape learning evolutionary computation based on CMA-ES. GECCO (Companion) 2017: 173-174 - [c9]Taku Hasegawa, Naoki Mori, Keinosuke Matsumoto:
Genetic programming with multi-layered population structure. GECCO (Companion) 2017: 229-230 - 2016
- [c8]Saya Fujino, Taku Hasegawa, Miki Ueno, Naoki Mori, Keinosuke Matsumoto:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 103-116 - [c7]Taku Hasegawa, Yuta Araki, Naoki Mori, Keinosuke Matsumoto:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 149-164 - [c6]Kento Tsukada, Taku Hasegawa, Naoki Mori, Keinosuke Matsumoto:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 417-429 - 2015
- [c5]Kazuyuki Inoue, Taku Hasegawa, Naoki Mori, Keinosuke Matsumoto:
Analyzing Exploration Exploitation Trade-off by means of P-I similarity index and Dictyostelium based Genetic Algorithm. CEC 2015: 2548-2555 - [c4]Taku Hasegawa, Kento Tsukada, Naoki Mori, Keinosuke Matsumoto:
Search dynamics of Fitness Landscape Learning Evolutionary Computation with two types of evolution control. CEC 2015: 2565-2572 - [c3]Taku Hasegawa, Kento Tsukada, Naoki Mori, Keinosuke Matsumoto:
Adaptive Evolution Control with P-I Similarity Index for Surrogate-assisted Evolutionary Computation. GECCO (Companion) 2015: 759-760 - [c2]Kazuyuki Inoue, Taku Hasegawa, Yuta Araki, Naoki Mori, Keinosuke Matsumoto:
Adaptive Control of Parameter-less Population Pyramid on the Local Distribution of Inferior Individuals. GECCO 2015: 863-870 - 2014
- [c1]Taku Hasegawa, Kaname Matsumura, Kaiki Tsuchie, Naoki Mori, Keinosuke Matsumoto:
Novel virtual fitness evaluation framework for fitness landscape learning evolutionary computation. GECCO (Companion) 2014: 107-108
Coauthor Index
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