Shin‐ichi Maeda
- Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
2017/04/13 by Takeru Miyato, Miyato, Takeru, Shin‐ichi Maeda +5 · 75 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Advanced Neural Network Applications
- DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback
2018/10/28 by Riku Arakawa, Sosuke Kobayashi, Arakawa, Riku +7 · 9 citations
Computer Science · Engineering · Neuroscience · #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Smart Grid Energy Management
- Robustness to Adversarial Perturbations in Learning from Incomplete Data
2019/05/24 by Amir Najafi, Najafi, Amir, Shin‐ichi Maeda +5 · 4 citations
Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Neural Multi-scale Image Compression
2018/05/16 by Ken Nakanishi, Nakanishi, Ken, Shin‐ichi Maeda +5 · 2 citations
Computer Science · #Advanced Data Compression Techniques #Advanced Image Processing Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks
2019/08/13 by Kohei Hayashi, Hayashi, Kohei, T. Yamaguchi +5 · 2 citations
Computer Science · Mathematics · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Tensor decomposition and applications
- Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network
2023/04/25 by Yuri Kinoshita, Kenta Oono, Kinoshita, Yuri +7 · 2 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Model Reduction and Neural Networks
- A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective?
2021/08/25 by Hiroaki Mikami, Mikami, Hiroaki, Kenji Fukumizu +13 · 1 citation
Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG)
- Warp-Refine Propagation: Semi-Supervised Auto-labeling via\n Cycle-consistency
2021/09/27 by Aditya Ganeshan, Ganeshan, Aditya, Alexis Vallet +13 · 1 citation
Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Video Surveillance and Tracking Methods
- A Bayesian encourages dropout
2014/12/22 by Shin‐ichi Maeda, Maeda, Shin-ichi · 2 citations
Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)
- Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks in Molecular Graph Analysis
2019/02/04 by Katsuhiko Ishiguro, Ishiguro, Katsuhiko, Shin‐ichi Maeda +3 · 1 citation
Computer Science · Materials Science · #Advanced Graph Neural Networks #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science