Shigeru Maya

According to our database, Shigeru Maya authored at least 11 papers between 2014 and 2020.

Collaborative distances:

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

2020

LTSpAUC: Learning Time-Series Shapelets for Partial AUC Maximization.

Akihiro Yamaguchi, Shigeru Maya, Kohei Maruchi, Ken Ueno

Big Data, 2020

LTSpAUC: Learning Time-series Shapelets for Optimizing Partial AUC.

Akihiro Yamaguchi, Shigeru Maya, Kohei Maruchi, Ken Ueno

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Lag-Aware Multivariate Time-Series Segmentation.

Shigeru Maya, Akihiro Yamaguchi, Kaneharu Nishino, Ken Ueno

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

RLTS: Robust Learning Time-Series Shapelets.

Akihiro Yamaguchi, Shigeru Maya, Ken Ueno

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Segmentation of Multi-State Compound Waveform and Extraction of Features for Anomaly Detection.

Topon Kumar Paul, Takeichiro Nishikawa, Shigeru Maya, Akihiro Itakura, Toshihide Kawachi, Akira Ogawa, Hiroshi Yokota

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2019

An 8 Bit 12.4 TOPS/W Phase-Domain MAC Circuit for Energy-Constrained Deep Learning Accelerators.

Yosuke Toyama, Kentaro Yoshioka, Koichiro Ban, Shigeru Maya, Akihide Sai, Kohei Onizuka

IEEE J. Solid State Circuits, 2019

dLSTM: a new approach for anomaly detection using deep learning with delayed prediction.

Shigeru Maya, Ken Ueno, Takeichiro Nishikawa

Int. J. Data Sci. Anal., 2019

2018

PhaseMAC: A 14 TOPS/W 8bit GRO Based Phase Domain MAC Circuit for in-Sensor-Computed Deep Learning Accelerators.

Kentaro Yoshioka, Yosuke Toyama, Koichiro Ban, Daisuke Yashima, Shigeru Maya, Akihide Sai, Kohei Onizuka

Proceedings of the 2018 IEEE Symposium on VLSI Circuits, 2018

OPOSSAM: Online Prediction of Stream Data Using Self-adaptive Memory.

Akihiro Yamaguchi, Shigeru Maya, Tatsuya Inagi, Ken Ueno

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2015

Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering.

Shigeru Maya, Kai Morino, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Predicting glaucoma progression using multi-task learning with heterogeneous features.

Shigeru Maya, Kai Morino, Kenji Yamanishi

Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014