Shin Matsushima

According to our database, Shin Matsushima authored at least 27 papers between 2010 and 2024.

Collaborative distances:

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

2024

Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables.

Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima

CoRR, 2024

2022

mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations.

Toyotaro Suzumura, Akiyoshi Sugiki, Hiroyuki Takizawa, Akira Imakura, Hiroshi Nakamura, Kenjiro Taura, Tomohiro Kudoh, Toshihiro Hanawa, Yuji Sekiya, Hill Hiroki Kobayashi, Shin Matsushima, Yohei Kuga, Ryo Nakamura, Renhe Jiang, Junya Kawase, Masatoshi Hanai, Hiroshi Miyazaki, Tsutomu Ishizaki, Daisuké Shimotoku, Daisuke Miyamoto, Kento Aida, Atsuko Takefusa, Takashi Kurimoto, Koji Sasayama, Naoya Kitagawa, Ikki Fujiwara, Yusuke Tanimura, Takayuki Aoki, Toshio Endo, Satoshi Ohshima, Keiichiro Fukazawa, Susumu Date, Toshihiro Uchibayashi

CoRR, 2022

Detection of Unobserved Common Cause in Discrete Data Based on the MDL Principle.

Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima

Proceedings of the IEEE International Conference on Big Data, 2022

2020

Grafting for combinatorial binary model using frequent itemset mining.

Taito Lee, Shin Matsushima, Kenji Yamanishi

Data Min. Knowl. Discov., 2020

Coordinate Descent Method for Log-linear Model on Posets.

Shota Hayashi, Mahito Sugiyama, Shin Matsushima

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019

Model Selection for Non-Negative Tensor Factorization with Minimum Description Length.

Yunhui Fu, Shin Matsushima, Kenji Yamanishi

Entropy, 2019

Selective Sampling-based Scalable Sparse Subspace Clustering.

Shin Matsushima, Maria Brbic

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Scaling Multinomial Logistic Regression via Hybrid Parallelism.

Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Traffic Risk Mining From Heterogeneous Road Statistics.

Koichi Moriya, Shin Matsushima, Kenji Yamanishi

IEEE Trans. Intell. Transp. Syst., 2018

Statistical Learnability of Generalized Additive Models based on Total Variation Regularization.

Shin Matsushima

CoRR, 2018

2017

Grafting for Combinatorial Boolean Model using Frequent Itemset Mining.

Taito Lee, Shin Matsushima, Kenji Yamanishi

CoRR, 2017

Sparse Graphical Modeling via Stochastic Complexity.

Kohei Miyaguchi, Shin Matsushima, Kenji Yamanishi

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem.

Shin Matsushima, Hyokun Yun, Xinhua Zhang, S. V. N. Vishwanathan

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Discovering potential traffic risks in Japan using a supervised learning approach.

Tatsuru Kobayashi, Shin Matsushima, Taito Lee, Kenji Yamanishi

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression.

Parameswaran Raman, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2016

Asynchronous Feature Extraction for Large-Scale Linear Predictors.

Shin Matsushima

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

WordRank: Learning Word Embeddings via Robust Ranking.

Shihao Ji, Hyokun Yun, Pinar Yanardag, Shin Matsushima, S. V. N. Vishwanathan

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Traffic Risk Mining Using Partially Ordered Non-Negative Matrix Factorization.

Taito Lee, Shin Matsushima, Kenji Yamanishi

Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Web Behavior Analysis Using Sparse Non-Negative Matrix Factorization.

Akihiro Demachi, Shin Matsushima, Kenji Yamanishi

Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

2015

Totally Corrective Boosting with Cardinality Penalization.

Vasil S. Denchev, Nan Ding, Shin Matsushima, S. V. N. Vishwanathan, Hartmut Neven

CoRR, 2015

2014

Distributed Stochastic Optimization of the Regularized Risk.

Shin Matsushima, Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2014

Feature-aware regularization for sparse online learning.

Hidekazu Oiwa, Shin Matsushima, Hiroshi Nakagawa

Sci. China Inf. Sci., 2014

2012

Linear support vector machines via dual cached loops.

Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Healing Truncation Bias: Self-Weighted Truncation Framework for Dual Averaging.

Hidekazu Oiwa, Shin Matsushima, Hiroshi Nakagawa

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011

Frequency-Aware Truncated Methods for Sparse Online Learning.

Hidekazu Oiwa, Shin Matsushima, Hiroshi Nakagawa

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010

Exact Passive-Aggressive Algorithm for Multiclass Classification Using Support Class.

Shin Matsushima, Nobuyuki Shimizu, Kazuhiro Yoshida, Takashi Ninomiya, Hiroshi Nakagawa

Proceedings of the SIAM International Conference on Data Mining, 2010

ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management.

Minoru Yoshida, Shin Matsushima, Shingo Ono, Issei Sato, Hiroshi Nakagawa

Proceedings of the CLEF 2010 LABs and Workshops, 2010