Yamaguchi, Shin'ya

1. Pruning Randomly Initialized Neural Networks with Iterative Randomization
   2021/06/17 by Chijiwa, Daiki, Yamaguchi, Shin'ya, Ida, Yasutoshi +2 · 2 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
2. Post-pre-training for Modality Alignment in Vision-Language Foundation Models
   2025/04/17 by Shin’ya Yamaguchi, Yamaguchi, Shin'ya, Sekitoshi Kanai +6 · 6 citations
   Computer Science · #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
3. On the Limitation of Diffusion Models for Synthesizing Training Datasets
   2023/11/22 by Shin’ya Yamaguchi, Yamaguchi, Shin'ya, Takuma Fukuda +1 · 2 citations
   Computer Science · Physics and Astronomy · #Advanced Mathematical Modeling in Engineering #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Model Reduction and Neural Networks
4. Test-time Adaptation for Regression by Subspace Alignment
   2024/10/04 by Adachi, Kazuki, Yamaguchi, Shin'ya, Kumagai, Atsutoshi +1 · 3 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
5. F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain
   2021/06/04 by Shin’ya Yamaguchi, Yamaguchi, Shin'ya, Sekitoshi Kanai +1 · 1 citation
   Computer Science · #Advanced Data Storage Technologies #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Neural Networks and Reservoir Computing #Speech Recognition and Synthesis #electronic engineering #information engineering
6. One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
   2022/07/21 by Kanai, Sekitoshi, Yamaguchi, Shin'ya, Yamada, Masanori +3 · 1 citation
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Toward Data Efficient Model Merging between Different Datasets without Performance Degradation
   2023/06/09 by Yamada, Masanori, Yamashita, Tomoya, Yamaguchi, Shin'ya +1 · 1 citation
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
8. Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff
   2023/08/31 by Satoshi Suzuki, Shin’ya Yamaguchi, Suzuki, Satoshi +11 · 1 citation
   Computer Science · Medicine · #Adversarial Robustness in Machine Learning #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
9. Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks
   2024/03/15 by Shin’ya Yamaguchi, Yamaguchi, Shin'ya, Sekitoshi Kanai +5 · 1 citation
   Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Neural Networks and Applications
10. Explanation Bottleneck Models
    2024/09/26 by Yamaguchi, Shin'ya, Nishida, Kosuke · 1 citation
    Decision Sciences · #Simulation Techniques and Applications
11. Zero-shot Concept Bottleneck Models
    2025/02/13 by Yamaguchi, Shin'ya, Nishida, Kosuke, Chijiwa, Daiki +1 · 1 citation
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)