Michinari Momma

Orcid: 0009-0005-4140-2350

According to our database1, Michinari Momma authored at least 23 papers between 2002 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
AdaSelection: Accelerating Deep Learning Training through Data Subsampling.
CoRR, 2023

Improving Product Search with Season-Aware Query-Product Semantic Similarity.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Federated Multi-Objective Learning.
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.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Multi-Label Learning to Rank through Multi-Objective Optimization.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Multi-Label Learning to Rank through Multi-Objective Optimization.
CoRR, 2022

Multi-task GNN for Substitute Identification.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

2020
Multi-objective Ranking via Constrained Optimization.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

2019
Multi-objective Relevance Ranking.
Proceedings of the SIGIR 2019 Workshop on eCommerce, 2019

2012
Influence Analysis in the Blogosphere
CoRR, 2012

2010
Ellipsoidal Support Vector Machines.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

2009
Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning.
Proceedings of the ICDM 2009, 2009

Linear Time Model Selection for Mixture of Heterogeneous Components.
Proceedings of the Advances in Machine Learning, 2009

2006
Constructing Orthogonal Latent Features for Arbitrary Loss.
Proceedings of the Feature Extraction - Foundations and Applications, 2006

2005
Efficient computations via scalable sparse kernel partial least squares and boosted latent features.
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.
SIGKDD Explor., 2003

Sparse Kernel Partial Least Squares Regression.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Efficiently Learning the Metric with Side-Information.
Proceedings of the Algorithmic Learning Theory, 14th International Conference, 2003

2002
A Pattern Search Method for Model Selection of Support Vector Regression.
Proceedings of the Second SIAM International Conference on Data Mining, 2002

MARK: a boosting algorithm for heterogeneous kernel models.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002


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