ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management. - Minoru Yoshida; Shin Matsushima; Shingo Ono; Issei Sato; Hiroshi Nakagawa (CLEF (Notebook Papers/LABs/Workshops), 2010)

Exact Passive-Aggressive Algorithm for Multiclass Classification Using Support Class. - Shin Matsushima; Nobuyuki Shimizu; Kazuhiro Yoshida; Takashi Ninomiya; Hiroshi Nakagawa (SDM, 2010)

Frequency-Aware Truncated Methods for Sparse Online Learning. - Hidekazu Oiwa; Shin Matsushima; Hiroshi Nakagawa (ECML/PKDD (2), 2011)

Healing Truncation Bias: Self-Weighted Truncation Framework for Dual Averaging. - Hidekazu Oiwa; Shin Matsushima; Hiroshi Nakagawa (ICDM, 2012)

Linear support vector machines via dual cached loops. - Shin Matsushima; S. V. N. Vishwanathan; Alexander J. Smola (KDD, 2012)

Feature-aware regularization for sparse online learning. - Hidekazu Oiwa; Shin Matsushima; Hiroshi Nakagawa (Sci. China Inf. Sci., 2014)

Distributed Stochastic Optimization of the Regularized Risk. - Shin Matsushima; Hyokun Yun; S. V. N. Vishwanathan (CoRR, 2014)

Totally Corrective Boosting with Cardinality Penalization. - Vasil S. Denchev; Nan Ding 002; Shin Matsushima; S. V. N. Vishwanathan; Hartmut Neven (CoRR, 2015)

Web Behavior Analysis Using Sparse Non-Negative Matrix Factorization. - Akihiro Demachi; Shin Matsushima; Kenji Yamanishi (DSAA, 2016)

Traffic Risk Mining Using Partially Ordered Non-Negative Matrix Factorization. - Taito Lee; Shin Matsushima; Kenji Yamanishi (DSAA, 2016)

WordRank: Learning Word Embeddings via Robust Ranking. - Shihao Ji 001; Hyokun Yun; Pinar Yanardag; Shin Matsushima; S. V. N. Vishwanathan (EMNLP, 2016)

Asynchronous Feature Extraction for Large-Scale Linear Predictors. - Shin Matsushima (ECML/PKDD (1), 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)

Discovering potential traffic risks in Japan using a supervised learning approach. - Tatsuru Kobayashi; Shin Matsushima; Taito Lee; Kenji Yamanishi (IEEE BigData, 2017)

Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem. - Shin Matsushima; Hyokun Yun; Xinhua Zhang; S. V. N. Vishwanathan (ECML/PKDD (1), 2017)

Sparse Graphical Modeling via Stochastic Complexity. - Kohei Miyaguchi; Shin Matsushima; Kenji Yamanishi (SDM, 2017)

Grafting for Combinatorial Boolean Model using Frequent Itemset Mining. - Taito Lee; Shin Matsushima; Kenji Yamanishi (CoRR, 2017)

Statistical Learnability of Generalized Additive Models based on Total Variation Regularization. - Shin Matsushima (CoRR, 2018)

Traffic Risk Mining From Heterogeneous Road Statistics. - Koichi Moriya; Shin Matsushima; Kenji Yamanishi (IEEE Trans. Intell. Transp. Syst., 2018)

Scaling Multinomial Logistic Regression via Hybrid Parallelism. - Parameswaran Raman; Sriram Srinivasan 004; Shin Matsushima; Xinhua Zhang; Hyokun Yun; S. V. N. Vishwanathan (KDD, 2019)

Selective Sampling-based Scalable Sparse Subspace Clustering. - Shin Matsushima; Maria Brbic (NeurIPS, 2019)

Model Selection for Non-Negative Tensor Factorization with Minimum Description Length. - Yunhui Fu; Shin Matsushima; Kenji Yamanishi (Entropy, 2019)

Coordinate Descent Method for Log-linear Model on Posets. - Shota Hayashi; Mahito Sugiyama; Shin Matsushima (DSAA, 2020)

Grafting for combinatorial binary model using frequent itemset mining. - Taito Lee; Shin Matsushima; Kenji Yamanishi (Data Min. Knowl. Discov., 2020)

Detection of Unobserved Common Cause in Discrete Data Based on the MDL Principle. - Masatoshi Kobayashi; Kohei Miyaguchi; Shin Matsushima (IEEE Big Data, 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; et al. (CoRR, 2022)

Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables. - Masatoshi Kobayashi; Kohei Miyaguchi; Shin Matsushima (CoRR, 2024)