Michinari Momma

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 15

Top Topics

Unconstrained Optimization

Sample Complexity

Recommender Systems

Top Venues

WWW (Companion Volume)

Publications

Tianchen Zhou, Hairi, Haibo Yang, Jia Liu, Tian Tong, Fan Yang, Michinari Momma, Yan Gao
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning. CoRR (2024)
Minghe Zhang, Chaosheng Dong, Jinmiao Fu, Tianchen Zhou, Jia Liang, Jia Liu, Bo Liu, Michinari Momma, Bryan Wang, Yan Gao, Yi Sun
AdaSelection: Accelerating Deep Learning Training through Data Subsampling. CoRR (2023)
Debabrata Mahapatra, Chaosheng Dong, Yetian Chen, Michinari Momma
Multi-Label Learning to Rank through Multi-Objective Optimization. KDD (2023)
Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma
Federated Multi-Objective Learning. CoRR (2023)
Debabrata Mahapatra, Chaosheng Dong, Michinari Momma
Querywise Fair Learning to Rank through Multi-Objective Optimization. KDD (2023)
Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma
Federated Multi-Objective Learning. NeurIPS (2023)
Haoming Chen, Yetian Chen, Jingjing Meng, Yang Jiao, Yikai Ni, Yan Gao, Michinari Momma, Yi Sun
Improving Product Search with Season-Aware Query-Product Semantic Similarity. WWW (Companion Volume) (2023)
Michinari Momma, Chaosheng Dong, Jia Liu
A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity. ICML (2022)
Minghong Fang, Jia Liu, Michinari Momma, Yi Sun
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. SACMAT (2022)
Debabrata Mahapatra, Chaosheng Dong, Yetian Chen, Deqiang Meng, Michinari Momma
Multi-Label Learning to Rank through Multi-Objective Optimization. CoRR (2022)
Minghong Fang, Jia Liu, Michinari Momma, Yi Sun
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. CoRR (2022)
Tong Jian, Fan Yang, Zhen Zuo, Wenbo Wang, Michinari Momma, Tong Zhao, Chaosheng Dong, Yan Gao, Yi Sun
Multi-task GNN for Substitute Identification. WWW (Companion Volume) (2022)
Michinari Momma, Alireza Bagheri Garakani, Nanxun Ma, Yi Sun
Multi-objective Ranking via Constrained Optimization. CoRR (2020)
Michinari Momma, Alireza Bagheri Garakani, Nanxun Ma, Yi Sun
Multi-objective Ranking via Constrained Optimization. WWW (Companion Volume) (2020)
Michinari Momma, Alireza Bagheri Garakani, Yi Sun
Multi-objective Relevance Ranking. eCOM@SIGIR (2019)
Michinari Momma, Yun Chi, Yuanqing Lin, Shenghuo Zhu, Tianbao Yang
Influence Analysis in the Blogosphere CoRR (2012)
Michinari Momma, Kohei Hatano, Hiroki Nakayama
Ellipsoidal Support Vector Machines. ACML (2010)
Michinari Momma, Satoshi Morinaga, Daisuke Komura
Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning. ICDM (2009)
Ryohei Fujimaki, Satoshi Morinaga, Michinari Momma, Kenji Aoki, Takayuki Nakata
Linear Time Model Selection for Mixture of Heterogeneous Components. ACML (2009)
Michinari Momma
Efficient computations via scalable sparse kernel partial least squares and boosted latent features. KDD (2005)
Joel Carleton, Daragh Hartnett, Joseph Milana, Michinari Momma, Joseph Sirosh, Gabriela Surpi
Model Builder for Predictive Analytics & Fair Isaac's approach to KDD Cup 2003. SIGKDD Explor. 5 (2) (2003)
Tijl De Bie, Michinari Momma, Nello Cristianini
Efficiently Learning the Metric with Side-Information. ALT (2003)
Michinari Momma, Kristin P. Bennett
Sparse Kernel Partial Least Squares Regression. COLT (2003)
Kristin P. Bennett, Michinari Momma, Mark J. Embrechts
MARK: a boosting algorithm for heterogeneous kernel models. KDD (2002)
Michinari Momma, Kristin P. Bennett
A Pattern Search Method for Model Selection of Support Vector Regression. SDM (2002)