- Hideaki Kim, "Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions," Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), December 2024.
- Takeshi Koshizuka, Masahiro Fujisawa, Yusuke Tanaka, Issei Sato, "Understanding the expressivity and trainability of Fourier Neural Operator," Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), December 2024.
- Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada, "Polyak Meets Parameter-free Clipped Gradient Descent," Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), December 2024.
- Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara, "AUC Maximization under Positive Distribution Shift," Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), December 2024.
- Jun Muramatsu, “A simple proof of multi-letter converse theorem for distributed lossless source coding,” Proceedings of the 2024 International Symposium on Information Theory and its Applications (ISITA 2024), November 2024.
- Lei Sun, Yusuke Tanaka, Tomoharu Iwata, "Meta-Learning under Task Shift," Transactions on Machine Learning Research (TMLR), October 2024.
- Hideo Bannai, Mitsuru Funakoshi, Diptarama Hendrian, Myuji Matsuda, Simon J. Puglisi, "Height-bounded Lempel-Ziv encodings" Proceedings of the 32nd Annual European Symposium on Algorithms (ESA 2024), pp.18:1-18:18, 2024.
- Yuto Nakashima, Dominik Koppl, Mitsuru Funakoshi, Shunsuke Inenaga, Hideo Bannai, "Edit and Alphabet-Ordering Sensitivity of Lex-parse," Proceedings of the 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024), pp.75:1-75:15, 2024.
- Tomoharu Iwata, Yusuke Tanaka, "Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics," Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI 2024), pp.4210-4218, 2024.
- 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 Hemoglobin A1c Changes: Machine-Learning Model Development," The Journal of Medical Internet Research Artificial Intelligence (JMIR AI), Vol.3, e56700, 2024.
- Yoichi Chikahara, Kansei Ushiyama, "Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation," Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence (UAI 2024), PMLR 244:749-762, 2024.
- Tomoharu Iwata, Ryo Nishikimi, Ryohei Shibue, Masahiro Nakano, Kunio Kashino, Hitonobu Tomoike, "Electrocardiographic Classification using Deep Learning with Lead Switching," Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2024), July 2024.
- Jun Muramatsu, "Distributed Source Coding Using Constrained-Random-Number Generators," Proceedings of the 2024 IEEE International Symposium on Information Theory (IEEE ISIT 2024), pp.1676-1681, 2024.
- Hiroshi Sawada, Kazuo Aoyama, Kohei Ikeda, "Zeroth-Order Optimization of Optical Neural Networks with Linear Combination Natural Gradient and Calibrated Model," Proceedings of the 61st ACM/IEEE Design Automation Conference (DAC 2024), Article No.23, pp.1-6, 2024.
- Tomoharu Iwata, Yoichi Chikahara, "Meta-learning for heterogeneous treatment effect estimation with closed-form solvers," Machine Learning, Vol.113, pp.6093-6114, May 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.
- 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), May 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), May 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.
- 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.
