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Shin Matsushima
Shin Matsushima
Verified email at ds.itc.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
Conference on Empirical Methods in Natural Language Processing, 2016
642016
Selective sampling-based scalable sparse subspace clustering
S Matsushima, M Brbic
Advances in Neural Information Processing Systems 32, 2019
612019
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
372010
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
302010
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
242012
mdx: A cloud platform for supporting data science and cross-disciplinary research collaborations
T Suzumura, A Sugiki, H Takizawa, A Imakura, H Nakamura, K Taura, ...
2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf …, 2022
212022
Traffic risk mining from heterogeneous road statistics
K Moriya, S Matsushima, K Yamanishi
IEEE Transactions on Intelligent Transportation Systems 19 (11), 3662-3675, 2018
202018
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
122016
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
92019
Distributed stochastic optimization of regularized risk via saddle-point problem
S Matsushima, H Yun, X Zhang, SVN Vishwanathan
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017
82017
Feature-aware regularization for sparse online learning
H Oiwa, S Matsushima, H Nakagawa
Science China Information Sciences 57, 1-21, 2014
62014
Frequency-aware truncated methods for sparse online learning
H Oiwa, S Matsushima, H Nakagawa
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011
62011
Model selection for non-negative tensor factorization with minimum description length
Y Fu, S Matsushima, K Yamanishi
Entropy 21 (7), 632, 2019
52019
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
52016
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
42020
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
42017
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
42016
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
Totally corrective boosting with cardinality penalization
VS Denchev, N Ding, S Matsushima, SVN Vishwanathan, H Neven
arXiv preprint arXiv:1504.01446, 2015
32015
Online Learning Under Capricious Feature Data Streams
H Zhou, S Matsushima
人工知能学会全国大会論文集 第 37 回 (2023), 2D4GS201-2D4GS201, 2023
12023
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