Shin'ya Yamaguchi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 31

Top Topics

Diffusion Models

Training Dataset

Top Venues

Publications

Shohei Enomoto, Naoya Hasegawa, Kazuki Adachi, Taku Sasaki, Shin'ya Yamaguchi, Satoshi Suzuki, Takeharu Eda
Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching. CoRR (2024)
Kazuki Adachi, Shohei Enomoto, Taku Sasaki, Shin'ya Yamaguchi
Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift. CoRR (2024)
Shin'ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks. CoRR (2024)
Shin'ya Yamaguchi
Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples. CoRR (2023)
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai
Covariance-Aware Feature Alignment with Pre-Computed Source Statistics for Test-Time Adaptation to Multiple Image Corruptions. ICIP (2023)
Shin'ya Yamaguchi
Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples. ACML (2023)
Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima
Regularizing Neural Networks with Meta-Learning Generative Models. CoRR (2023)
Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima
Regularizing Neural Networks with Meta-Learning Generative Models. NeurIPS (2023)
Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Kentaro Ohno, Yasutoshi Ida
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training. ICML (2023)
Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Sekitoshi Kanai, Naoki Makishima, Atsushi Ando, Ryo Masumura
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff. CoRR (2023)
Masanori Yamada, Tomoya Yamashita, Shin'ya Yamaguchi, Daiki Chijiwa
Revisiting Permutation Symmetry for Merging Models between Different Datasets. CoRR (2023)
Shin'ya Yamaguchi, Takuma Fukuda
On the Limitation of Diffusion Models for Synthesizing Training Datasets. CoRR (2023)
Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Sekitoshi Kanai, Naoki Makishima, Atsushi Ando, Ryo Masumura
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff. ICCV (2023)
Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima
Transfer Learning with Pre-trained Conditional Generative Models. CoRR (2022)
Kazuki Adachi, Shin'ya Yamaguchi
Learning Robust Convolutional Neural Networks with Relevant Feature Focusing via Explanations. CoRR (2022)
Daiki Chijiwa, Shin'ya Yamaguchi, Atsutoshi Kumagai, Yasutoshi Ida
Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks. NeurIPS (2022)
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai
Covariance-aware Feature Alignment with Pre-computed Source Statistics for Test-time Adaptation. CoRR (2022)
Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Yasutoshi Ida
Switching One-Versus-the-Rest Loss to Increase the Margin of Logits for Adversarial Robustness. CoRR (2022)
Kazuki Adachi, Shin'ya Yamaguchi
Learning Robust Convolutional Neural Networks with Relevant Feature Focusing Via Explanations. ICME (2022)
Daiki Chijiwa, Shin'ya Yamaguchi, Atsutoshi Kumagai, Yasutoshi Ida
Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks. CoRR (2022)
Daiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue
Pruning Randomly Initialized Neural Networks with Iterative Randomization. CoRR (2021)
Daiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue
Pruning Randomly Initialized Neural Networks with Iterative Randomization. NeurIPS (2021)
Shin'ya Yamaguchi, Sekitoshi Kanai, Tetsuya Shioda, Shoichiro Takeda
Image Enhanced Rotation Prediction for Self-Supervised Learning. ICIP (2021)
Shin'ya Yamaguchi, Sekitoshi Kanai
F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain. ICCV (2021)
Sekitoshi Kanai, Masanori Yamada, Shin'ya Yamaguchi, Hiroshi Takahashi, Yasutoshi Ida
Constraining Logits by Bounded Function for Adversarial Robustness. IJCNN (2021)
Shin'ya Yamaguchi, Sekitoshi Kanai
F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain. CoRR (2021)
Shin'ya Yamaguchi, Sekitoshi Kanai, Takeharu Eda
Effective Data Augmentation with Multi-Domain Learning GANs. AAAI (2020)
Sekitoshi Kanai, Masanori Yamada, Shin'ya Yamaguchi, Hiroshi Takahashi, Yasutoshi Ida
Constraining Logits by Bounded Function for Adversarial Robustness. CoRR (2020)
Shin'ya Yamaguchi, Sekitoshi Kanai, Takeharu Eda
Effective Data Augmentation with Multi-Domain Learning GANs. CoRR (2019)
Shin'ya Yamaguchi, Sekitoshi Kanai, Tetsuya Shioda, Shoichiro Takeda
Multiple Pretext-Task for Self-Supervised Learning via Mixing Multiple Image Transformations. CoRR (2019)
Shin'ya Yamaguchi, Kimio Kuramitsu
A Fusion Technique of Schema and Syntax Rules for Validating Open Data. ACIIDS (Extended Posters) (2017)