Imaizumi, Masaaki

1. Deep Neural Networks Learn Non-Smooth Functions Effectively
   2018/02/13 by Masaaki Imaizumi, Imaizumi, Masaaki, Kenji Fukumizu +1 · 3 citations
   Computer Science · #FOS: Computer and information sciences #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Neural Networks and Applications
2. Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces
   2019/10/15 by Akiyoshi Sannai, Sannai, Akiyoshi, Masaaki Imaizumi +3 · 3 citations
   Computer Science · Engineering · #3D Shape Modeling and Analysis #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Distillation of Discrete Diffusion through Dimensional Correlations
   2024/10/11 by Satoshi Hayakawa, Hayakawa, Satoshi, Yuhta Takida +7 · 8 citations
   Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Process Optimization and Integration
4. Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency
   2021/02/05 by Masatoshi Uehara, Uehara, Masatoshi, Masaaki Imaizumi +9 · 6 citations
   Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Formal Methods in Verification #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Software Reliability and Analysis Research #Statistics Theory (math.ST)
5. Distribution-on-Distribution Regression with Wasserstein Metric: Multivariate Gaussian Case
   2023/07/12 by Okano, Ryo, Imaizumi, Masaaki · 3 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #Statistics Theory (math.ST)
6. Doubly Decomposing Nonparametric Tensor Regression
   2015/06/19 by Masaaki Imaizumi, Kohei Hayashi, Imaizumi, Masaaki +1 · 2 citations
   Mathematics · Computer Science · Engineering · #Tensor decomposition and applications #Gaussian Processes and Bayesian Inference #Sparse and Compressive Sensing Techniques
7. Instrumental Variable Regression via Kernel Maximum Moment Loss
   2020/10/15 by Zhang, Rui, Imaizumi, Masaaki, Schölkopf, Bernhard +1 · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
8. SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
   2023/01/30 by Yuhta Takida, Takida, Yuhta, Masaaki Imaizumi +10 · 3 citations
   Computer Science · #AI in cancer detection #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG)
9. High-dimensional Contextual Bandit Problem without Sparsity
   2023/06/19 by Junpei Komiyama, Komiyama, Junpei, Masaaki Imaizumi +1 · 2 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
10. Automatic Domain Adaptation by Transformers in In-Context Learning
    2024/05/27 by Ryuichiro Hataya, Kota Matsui, Hataya, Ryuichiro +3 · 1 voice · 2 citations
    Computer Science · #cs.LG #stat.ML
11. PCA-based estimation for functional linear regression with functional responses
    2016/09/01 by Masaaki Imaizumi, Imaizumi, Masaaki, Kengo Kato +1 · 1 citation
    Mathematics · #Statistical Methods and Inference #Advanced Statistical Methods and Models #Statistical Methods and Bayesian Inference
12. A simple method to construct confidence bands in functional linear regression
    2016/12/22 by Imaizumi, Masaaki, Kato, Kengo · 1 citation
    #FOS: Mathematics #Statistics Theory (math.ST)
13. Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces
    2020/11/04 by Masaaki Imaizumi, Imaizumi, Masaaki, Kenji Fukumizu +1 · 1 citation
    Computer Science · Materials Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning in Materials Science
14. Exponential escape efficiency of SGD from sharp minima in non-stationary regime
    2021/11/07 by Hikaru Ibayashi, Ibayashi, Hikaru, Masaaki Imaizumi +1 · 1 citation
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
15. On Tensor Train Rank Minimization: Statistical Efficiency and Scalable Algorithm
    2017/08/01 by Masaaki Imaizumi, Imaizumi, Masaaki, Takanori Maehara +3 · 1 citation
    Engineering · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Sparse and Compressive Sensing Techniques #Tensor decomposition and applications
16. Benign Overfitting in Time Series Linear Models with Over-Parameterization
    2022/04/18 by Shogo Nakakita, Masaaki Imaizumi, Nakakita, Shogo +1 · 2 citations
    Mathematics · Economics, Econometrics and Finance · Computer Science · #Statistical Methods and Inference #Financial Risk and Volatility Modeling #Bayesian Methods and Mixture Models
17. Best Arm Identification with Contextual Information under a Small Gap
    2022/09/15 by Masahiro Kato, Kato, Masahiro, Masaaki Imaizumi +5 · 1 citation
    Decision Sciences · Economics, Econometrics and Finance · Mathematics · #Advanced Bandit Algorithms Research #Advanced Causal Inference Techniques #Econometrics (econ.EM) #Economic Policies and Impacts #FOS: Computer and information sciences #FOS: Economics and business #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
18. Effect of Weight Quantization on Learning Models by Typical Case Analysis
    2024/01/30 by Shuhei Kashiwamura, Ayaka Sakata, Kashiwamura, Shuhei +3 · 2 citations
    Computer Science · #Advanced Neural Network Applications #Stochastic Gradient Optimization Techniques #Big Data and Digital Economy
19. Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion
    2025/10/06 by Satoshi Hayakawa, Yuhta Takida, Hayakawa, Satoshi +7 · 2 citations
    Computer Science · Medicine · #Generative Adversarial Networks and Image Synthesis #Advanced Neuroimaging Techniques and Applications #Medical Image Segmentation Techniques
20. Approximation of Permutation Invariant Polynomials by Transformers: Efficient Construction in Column-Size
    2025/02/17 by Takeshita, Naoki, Imaizumi, Masaaki · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Functional Analysis (math.FA) #Machine Learning (cs.LG)
21. Fast Convergence on Perfect Classification for Functional Data
    2021/04/07 by Wakayama, Tomoya, Imaizumi, Masaaki · 1 citation
    #FOS: Mathematics #Statistics Theory (math.ST)