| 2026 | SIGIR | Behavioral Feature Boosting via Substitute Relationships for E-commerce Search. | Chaosheng Dong, Michinari Momma, Yijia Wang, Yan Gao, Yi Sun |
| 2025 | SIGIR | MO-LightGBM: A Library for Multi-objective Learning to Rank with LightGBM. | Chaosheng Dong, Michinari Momma |
| 2025 | UAI | STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning. | Zhuqing Liu, Chaosheng Dong, Michinari Momma, Simone Shao, Shaoyuan Xu, Yan Gao, Haibo Yang, Jia Liu |
| 2024 | ICDM | Transitivity-Encoded Graph Attention Networks for Complementary Item Recommendations. | Jin Shang, Yang Jiao, Chenghuan Guo, Minghao Sun, Yan Gao, Jia Liu, Michinari Momma, Itetsu Taru, Yi Sun |
| 2024 | ICML | Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning. | Tianchen Zhou, Hairi, Haibo Yang, Jia Liu, Tian Tong, Fan Yang, Michinari Momma, Yan Gao |
| 2023 | KDD | Multi-Label Learning to Rank through Multi-Objective Optimization. | Debabrata Mahapatra, Chaosheng Dong, Yetian Chen, Michinari Momma |
| 2023 | KDD | Querywise Fair Learning to Rank through Multi-Objective Optimization. | Debabrata Mahapatra, Chaosheng Dong, Michinari Momma |
| 2023 | WWW | Improving Product Search with Season-Aware Query-Product Semantic Similarity. | Haoming Chen, Yetian Chen, Jingjing Meng, Yang Jiao, Yikai Ni, Yan Gao, Michinari Momma, Yi Sun |
| 2022 | ICML | A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity. | Michinari Momma, Chaosheng Dong, Jia Liu |
| 2022 | WWW | Multi-task GNN for Substitute Identification. | Tong Jian, Fan Yang, Zhen Zuo, Wenbo Wang, Michinari Momma, Tong Zhao, Chaosheng Dong, Yan Gao, Yi Sun |
| 2022 | SACMAT | FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. | Minghong Fang, Jia Liu, Michinari Momma, Yi Sun |
| 2020 | WWW | Multi-objective Ranking via Constrained Optimization. | Michinari Momma, Alireza Bagheri Garakani, Nanxun Ma, Yi Sun |
| 2019 | SIGIR | Multi-objective Relevance Ranking. | Michinari Momma, Alireza Bagheri Garakani, Yi Sun |
| 2009 | ACML | Linear Time Model Selection for Mixture of Heterogeneous Components. | Ryohei Fujimaki, Satoshi Morinaga, Michinari Momma, Kenji Aoki, Takayuki Nakata |
| 2009 | ICDM | Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning. | Michinari Momma, Satoshi Morinaga, Daisuke Komura |
| 2005 | KDD | Efficient computations via scalable sparse kernel partial least squares and boosted latent features. | Michinari Momma |
| 2003 | ALT | Efficiently Learning the Metric with Side-Information. | Tijl De Bie, Michinari Momma, Nello Cristianini |
| 2003 | COLT | Sparse Kernel Partial Least Squares Regression. | Michinari Momma, Kristin P. Bennett |
| 2002 | KDD | MARK: a boosting algorithm for heterogeneous kernel models. | Kristin P. Bennett, Michinari Momma, Mark J. Embrechts |
| 2002 | SDM | A Pattern Search Method for Model Selection of Support Vector Regression. | Michinari Momma, Kristin P. Bennett |