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Rio Yokota

  1. Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks
    2018/11/29 by Kazuki Osawa, Yohei Tsuji, Osawa, Kazuki +9 · 1 voice · 1 citation
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #cs.CV #cs.LG #stat.ML
  2. Practical Deep Learning with Bayesian Principles
    2019/06/06 by Kazuki Osawa, Osawa, Kazuki, Siddharth Swaroop +11 · 11 citations
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. Variational Learning is Effective for Large Deep Networks
    2024/02/27 by Yuesong Shen, Nico Daheim, Shen, Yuesong +18 · 1 voice · 15 citations
    Computer Science · #Generative Adversarial Networks and Image Synthesis
  4. RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering
    2021/04/01 by Shun Iwase, Xingyu Liu, Iwase, Shun +7 · 7 citations
    Computer Science · Engineering · #3D Shape Modeling and Analysis #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition
  5. DGEMM on Integer Matrix Multiplication Unit
    2023/06/21 by Hiroyuki Ootomo, Ootomo, Hiroyuki, Katsuhisa Ozaki +3 · 11 citations
    Computer Science · #Advanced Data Storage Technologies #Distributed #FOS: Computer and information sciences #Parallel #Parallel Computing and Optimization Techniques #Quantum Computing Algorithms and Architecture #and Cluster Computing (cs.DC)
  6. DGEMM on integer matrix multiplication unit
    2024/03/15 by Hiroyuki Ootomo, Katsuhisa Ozaki, Rio Yokota · 1 voice · 4 citations
    Computer Science · Mathematics · #Matrix Theory and Algorithms #Quantum Computing Algorithms and Architecture #Tensor decomposition and applications
  7. ASDL: A Unified Interface for Gradient Preconditioning in PyTorch
    2023/05/08 by Kazuki Osawa, Osawa, Kazuki, Satoki Ishikawa +7 · 3 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Matrix Theory and Algorithms #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
  8. Scalable Linear Time Dense Direct Solver for 3-D Problems Without Trailing Sub-Matrix Dependencies
    2022/08/23 by Qianxiang Ma, Sameer Deshmukh, Ma, Qianxiang +3 · 2 citations
    Computer Science · Engineering · Physics and Astronomy · #Electromagnetic Scattering and Analysis #Electromagnetic Simulation and Numerical Methods #FOS: Mathematics #Matrix Theory and Algorithms #Numerical Analysis (math.NA)
  9. Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
    2025/02/26 by Taishi Nakamura, Takuya Akiba, Nakamura, Taishi +9 · 6 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Domain Adaptation and Few-Shot Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mobile Crowdsensing and Crowdsourcing
  10. Fast Multipole Method as a Matrix-Free Hierarchical Low-Rank Approximation
    2016/02/06 by Rio Yokota, Yokota, Rio, Huda Ibeid +3 · 1 citation
    Engineering · Environmental Science · Physics and Astronomy · #65Y20 #68Q25 #D.1.3 #Electromagnetic Scattering and Analysis #FOS: Mathematics #G.1.0 #G.1.2 #G.1.3 #G.1.4 #G.1.8 #G.1.9 #G.4 #Numerical Analysis (math.NA) #Soil Moisture and Remote Sensing #Sparse and Compressive Sensing Techniques
  11. Rewriting Pre-Training Data Boosts LLM Performance in Math and Code
    2025/05/05 by Kazuki Fujii, Y. Tajima, Fujii, Kazuki +29 · 7 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Digital Rights Management and Security #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mathematics, Computing, and Information Processing #Natural Language Processing Techniques
  12. Building a Large Japanese Web Corpus for Large Language Models
    2024/04/27 by Naoaki Okazaki, Kakeru Hattori, Okazaki, Naoaki +17 · 2 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling
  13. Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code
    2024/03/30 by Taishi Nakamura, Mayank Mishra, Nakamura, Taishi +86 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Library Science and Information Systems #Machine Learning (cs.LG)
  14. SegRCDB: Semantic Segmentation via Formula-Driven Supervised Learning
    2023/09/29 by Risa Shinoda, Ryo Hayamizu, Shinoda, Risa +9 · 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 #Multimodal Machine Learning Applications
  15. Epipolar-Guided Deep Object Matching for Scene Change Detection
    2020/07/30 by Kento Doi, Doi, Kento, Ryuhei Hamaguchi +9 · 1 citation
    Computer Science · #Advanced Image and Video Retrieval Techniques #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications
  16. Variational Low-Rank Adaptation Using IVON
    2024/11/07 by Bai Cong, Nico Daheim, Cong, Bai +11 · 2 citations
    Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Image Processing Techniques and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Reservoir Computing #Optical Coherence Tomography Applications
  17. Accelerating Large Language Model Training with 4D Parallelism and Memory Consumption Estimator
    2024/11/10 by Kazuki Fujii, Fujii, Kazuki, Kohei Watanabe +3 · 1 citation
    Computer Science · #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Parallel #Topic Modeling #and Cluster Computing (cs.DC)