知能創発環境研究グループ
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2024   2023   2022   2021   2020   2019   2018   2017   2016   2015   2014   2013   2012   2011   2010   2009   2008   ∼2007  

  • Eri Nakahara, Takayuki Oka, Hiroshi Kawaguchi, Kouzou Nakamura, Sakae Tanaka, Noriko Yoshimura, Seiko Itaka, Akihiro Chiba, Hisashi Kurasawa, Akinori Fujino, Nagisa Shiomi, Hirohito Maruyama, Chiaki Horii, Shigeyuki Muraki, "Identifying Factors Associated with Locomotive Syndrome Using Machine Learning Methods: The third survey of the research on osteoarthritis/osteoporosis against disability study," Geriatrics & Gerontology International (GGI), Vol.24, Issue 8, pp.806-813, 2024.
  • Hisashi Kurasawa, Kayo Waki, Tomohisa Seki, Akihiro Chiba, Akinori Fujino, Katsuyoshi Hayashi, Eri Nakahara, Tsuneyuki Haga, Takashi Noguchi, Kazuhiko Ohe, "Enhancing Type 2 Diabetes Treatment Decisions with Interpretable Machine Learning Models for Predicting HbA1c Changes: Machine-Learning Model Development," The Journal of Medical Internet Research Artificial Intelligence (JMIR AI), Vol.3, e56700, 2024.
  • Takumi Fukami, Tomoya Murata, Kenta Niwa, Iifan Tyou, "DP-Norm: Differential Privacy Primal-Dual Algorithm for Decentralized Federated Learning," IEEE Transactions on Information Forensics and Security, VOl.19, pp.5783-5797, 2024.
  • Kenta Niwa, Hiro Ishii, Hiroshi Sawada, Akinori Fujino, Noboru Harada, and Rio Yokota, "Natural Gradient Primal-Dual Method for Decentralized Learning," IEEE Transactions on Signal and Information Processing over Networks, Vol.10, pp.417-433, 2024.
  • Tomoharu Iwata, Atsutoshi Kumagai, "Meta-learning to calibrate Gaussian processes with deep kernels for regression uncertainty estimation," Neurocomputing, Vol.579, 127441, 2024.
  • Yuya Yoshikawa, Tomoharu Iwata, "Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers," Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), pp.370-378, 2024.
  • Futoshi Futami, Tomoharu Iwata, "Information-theoretic Analysis of Bayesian Test Data Sensitivity," Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), pp.1099-1107, 2024.
  • Tomoya Murata, Kenta Niwa, Takumi Fukami, Iifan Tyou, "Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity," Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), 2024.
  • Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn, "On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation," Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), 2024.
  • Iifan Tyou, Tomoya Murata, Takumi Fukami, Yuki Takezawa, Kenta Niwa, "A Localized Primal-Dual Method for Centralized/Decentralized Federated Learning Robust to Data Heterogeneity," IEEE Transaction on Signals and Information Processing over Networks, Vol.10, pp.94-107, 2024.
  • Naoki Marumo, Takeru Matsuda, Yuto Miyatake, "Modelling the discretization error of initial value problems using the Wishart distribution," Applied Mathematics Letters, Vol.147, Article 108833, 2024.
  • Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara, "Zero-Shot Task Adaptation with Relevant Feature Information," Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vol.38, No.12, pp.13283-13291, 2024.
  • Shoichiro Takeda, Yasunori Akagi, Naoki Marumo, Kenta Niwa, "Optimal Transport with Cyclic Symmetry," Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vol.38, No.14, pp.15211-15221, 2024.
  • Shunsuke Horii, Yoichi Chikahara, "Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model," Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vol.38, No.18, pp.20420-20429, 2024.