Shin Matsushima
Shin Matsushima
Verified email at mist.i.u-tokyo.ac.jp - Homepage
Title
Cited by
Cited by
Year
Wordrank: Learning word embeddings via robust ranking
S Ji, H Yun, P Yanardag, S Matsushima, SVN Vishwanathan
arXiv preprint arXiv:1506.02761, 2015
382015
ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management.
M Yoshida, S Matsushima, S Ono, I Sato, H Nakagawa
CLEF (Notebook Papers/LABs/Workshops) 170, 2010
362010
Linear support vector machines via dual cached loops
S Matsushima, SVN Vishwanathan, AJ Smola
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
212012
Exact passive-aggressive algorithm for multiclass classification using support class
S Matsushima, N Shimizu, K Yoshida, T Ninomiya, H Nakagawa
Proceedings of the 2010 SIAM International Conference on Data Mining, 303-314, 2010
152010
DS-MLR: exploiting double separability for scaling up distributed multinomial logistic regression
P Raman, S Srinivasan, S Matsushima, X Zhang, H Yun, ...
arXiv preprint arXiv:1604.04706, 2016
92016
Traffic risk mining from heterogeneous road statistics
K Moriya, S Matsushima, K Yamanishi
IEEE Transactions on Intelligent Transportation Systems 19 (11), 3662-3675, 2018
62018
Distributed stochastic optimization of the regularized risk
S Matsushima, H Yun, X Zhang, SVN Vishwanathan
arXiv preprint arXiv:1406.4363, 2014
52014
Frequency-aware truncated methods for sparse online learning
H Oiwa, S Matsushima, H Nakagawa
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
52011
Healing truncation bias: self-weighted truncation framework for dual averaging
H Oiwa, S Matsushima, H Nakagawa
2012 IEEE 12th International Conference on Data Mining, 575-584, 2012
42012
Scaling multinomial logistic regression via hybrid parallelism
P Raman, S Srinivasan, S Matsushima, X Zhang, H Yun, ...
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
32019
Selective sampling-based scalable sparse subspace clustering
S Matsushima, M Brbic
Advances in Neural Information Processing Systems, 12416-12425, 2019
22019
Sparse graphical modeling via stochastic complexity
K Miyaguchi, S Matsushima, K Yamanishi
Proceedings of the 2017 SIAM International Conference on Data Mining, 723-731, 2017
22017
Web behavior analysis using sparse non-negative matrix factorization
A Demachi, S Matsushima, K Yamanishi
2016 IEEE International Conference on Data Science and Advanced Analytics …, 2016
22016
Traffic Risk Mining Using Partially Ordered Non-negative Matrix Factorization
T Lee, S Matsushima, K Yamanishi
2016 IEEE International Conference on Data Science and Advanced Analytics …, 2016
22016
Feature-aware regularization for sparse online learning
H Oiwa, S Matsushima, H Nakagawa
Science China Information Sciences 57 (5), 1-21, 2014
22014
Statistical learnability of generalized additive models based on total variation regularization
S Matsushima
arXiv preprint arXiv:1802.03001, 2018
12018
Grafting for Combinatorial Boolean Model using Frequent Itemset Mining
T Lee, S Matsushima, K Yamanishi
arXiv preprint arXiv:1711.02478, 2017
12017
Totally corrective boosting with cardinality penalization
VS Denchev, N Ding, S Matsushima, SVN Vishwanathan, H Neven
arXiv preprint arXiv:1504.01446, 2015
12015
Grafting for combinatorial binary model using frequent itemset mining
T Lee, S Matsushima, K Yamanishi
Data Mining and Knowledge Discovery 34 (1), 101-123, 2020
2020
Model Selection for Non-Negative Tensor Factorization with Minimum Description Length
Y Fu, S Matsushima, K Yamanishi
Entropy 21 (7), 632, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–20