| 2026 | ACL | Why Mean Pooling Works: Quantifying Second-Order Collapse in Text Embeddings. | Tomomasa Hara, Hiroto Kurita, Masaaki Imaizumi, Kentaro Inui, Sho Yokoi |
| 2025 | AISTATS | Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient Descent. | Guillaume Braun, Minh Ha Quang, Masaaki Imaizumi |
| 2025 | ICML | Distillation of Discrete Diffusion through Dimensional Correlations. | Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji |
| 2024 | ICLR | SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer. | Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji |
| 2024 | ISIT | Effect of Weight Quantization on Learning Models by Typical Case Analysis. | Shuhei Kashiwamura, Ayaka Sakata, Masaaki Imaizumi |
| 2023 | AISTATS | Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics. | Masahiro Kato, Masaaki Imaizumi, Kentaro Minami |
| 2022 | ICLR | Learning Causal Models from Conditional Moment Restrictions by Importance Weighting. | Masahiro Kato, Masaaki Imaizumi, Kenichiro McAlinn, Shota Yasui, Haruo Kakehi |
| 2021 | UAI | Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces. | Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano |
| 2020 | AISTATS | On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis. | Kohei Hayashi, Masaaki Imaizumi, Yuichi Yoshida |
| 2019 | AISTATS | Deep Neural Networks Learn Non-Smooth Functions Effectively. | Masaaki Imaizumi, Kenji Fukumizu |
| 2018 | AISTATS | Statistically Efficient Estimation for Non-Smooth Probability Densities. | Masaaki Imaizumi, Takanori Maehara, Yuichi Yoshida |
| 2017 | ICML | Tensor Decomposition with Smoothness. | Masaaki Imaizumi, Kohei Hayashi |
| 2017 | IJCAI | Factorized Asymptotic Bayesian Policy Search for POMDPs. | Masaaki Imaizumi, Ryohei Fujimaki |
| 2016 | ICML | Doubly Decomposing Nonparametric Tensor Regression. | Masaaki Imaizumi, Kohei Hayashi |