Michinari Momma

According to our database, Michinari Momma authored at least 27 papers between 2002 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach.

Hairi, Jiao Yang, Tianchen Zhou, Haibo Yang, Chaosheng Dong, Fan Yang, Michinari Momma, Yan Gao, Jia Liu

CoRR, July, 2025

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

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

MO-LightGBM: A Library for Multi-objective Learning to Rank with LightGBM.

Chaosheng Dong, Michinari Momma

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

2024

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Proceedings of the IEEE International Conference on Data Mining, 2024

2023

AdaSelection: Accelerating Deep Learning Training through Data Subsampling.

Minghe Zhang, Chaosheng Dong, Jinmiao Fu, Tianchen Zhou, Jia Liang, Jia Liu, Bo Liu, Michinari Momma, Bryan Wang, Yan Gao, Yi Sun

CoRR, 2023

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

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Federated Multi-Objective Learning.

Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Querywise Fair Learning to Rank through Multi-Objective Optimization.

Debabrata Mahapatra, Chaosheng Dong, Michinari Momma

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Multi-Label Learning to Rank through Multi-Objective Optimization.

Debabrata Mahapatra, Chaosheng Dong, Yetian Chen, Michinari Momma

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Multi-Label Learning to Rank through Multi-Objective Optimization.

Debabrata Mahapatra, Chaosheng Dong, Yetian Chen, Deqiang Meng, Michinari Momma

CoRR, 2022

Multi-task GNN for Substitute Identification.

Tong Jian, Fan Yang, Zhen Zuo, Wenbo Wang, Michinari Momma, Tong Zhao, Chaosheng Dong, Yan Gao, Yi Sun

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data.

Minghong Fang, Jia Liu, Michinari Momma, Yi Sun

Proceedings of the SACMAT '22: The 27th ACM Symposium on Access Control Models and Technologies, New York, NY, USA, June 8, 2022

A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity.

Michinari Momma, Chaosheng Dong, Jia Liu

Proceedings of the International Conference on Machine Learning, 2022

2020

Multi-objective Ranking via Constrained Optimization.

Michinari Momma, Alireza Bagheri Garakani, Nanxun Ma, Yi Sun

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

2019

Multi-objective Relevance Ranking.

Michinari Momma, Alireza Bagheri Garakani, Yi Sun

Proceedings of the SIGIR 2019 Workshop on eCommerce, 2019

2012

Influence Analysis in the Blogosphere

Michinari Momma, Yun Chi, Yuanqing Lin, Shenghuo Zhu, Tianbao Yang

CoRR, 2012

2010

Ellipsoidal Support Vector Machines.

Michinari Momma, Kohei Hatano, Hiroki Nakayama

Proceedings of the 2nd Asian Conference on Machine Learning, 2010

2009

Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning.

Michinari Momma, Satoshi Morinaga, Daisuke Komura

Proceedings of the ICDM 2009, 2009

Linear Time Model Selection for Mixture of Heterogeneous Components.

Ryohei Fujimaki, Satoshi Morinaga, Michinari Momma, Kenji Aoki, Takayuki Nakata

Proceedings of the Advances in Machine Learning, 2009

2006

Constructing Orthogonal Latent Features for Arbitrary Loss.

Michinari Momma, Kristin P. Bennett

Proceedings of the Feature Extraction - Foundations and Applications, 2006

2005

Efficient computations via scalable sparse kernel partial least squares and boosted latent features.

Michinari Momma

Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

2003

Model Builder for Predictive Analytics & Fair Isaac's approach to KDD Cup 2003.

Joel Carleton, Daragh Hartnett, Joseph Milana, Michinari Momma, Joseph Sirosh, Gabriela Surpi

SIGKDD Explor., 2003

Sparse Kernel Partial Least Squares Regression.

Michinari Momma, Kristin P. Bennett

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Efficiently Learning the Metric with Side-Information.

Tijl De Bie, Michinari Momma, Nello Cristianini

Proceedings of the Algorithmic Learning Theory, 14th International Conference, 2003

2002

A Pattern Search Method for Model Selection of Support Vector Regression.

Michinari Momma, Kristin P. Bennett

Proceedings of the Second SIAM International Conference on Data Mining, 2002

MARK: a boosting algorithm for heterogeneous kernel models.

Kristin P. Bennett, Michinari Momma, Mark J. Embrechts

Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002