Sekitoshi Kanai

发表

Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks pdf

Shuichi Adachi, Yasutoshi Ida, Sekitoshi Kanai, 2019, AAAI.

Fast Random Forest Algorithm via Incremental Upper Bound

Yasuhiro Fujiwara, Atsutoshi Kumagai, Naonori Ueda, 2019, CIKM.

Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance

Koh Takeuchi, Hisashi Kashima, Yasuhiro Fujiwara, 2020, ICML.

Sigsoftmax: Reanalysis of the Softmax Bottleneck

Yasuhiro Fujiwara, Shuichi Adachi, Sekitoshi Kanai, 2018, NeurIPS.

Effective Data Augmentation with Multi-Domain Learning GANs pdf

Takeharu Eda, Shin'ya Yamaguchi, Sekitoshi Kanai, 2019, AAAI.

Multiple Pretext-Task for Self-Supervised Learning via Mixing Multiple Image Transformations pdf

Shoichiro Takeda, Shin'ya Yamaguchi, Sekitoshi Kanai, 2019, ArXiv.

Identification input design for simultaneous estimation of head-related transfer functions

Kentaro Matsui, Shuichi Adachi, Sekitoshi Kanai, 2014, 2014 Proceedings of the SICE Annual Conference (SICE).

Low-complexity simultaneous estimation of head-related transfer functions by prediction error method

Kentaro Matsui, Shuichi Adachi, Sekitoshi Kanai, 2016 .

Efficient Data Point Pruning for One-Class SVM

Naonori Ueda, Yasuhiro Fujiwara, Yasutoshi Ida, 2019, AAAI.

Efficient Algorithm for the b-Matching Graph

Naonori Ueda, Yasuhiro Fujiwara, Atsutoshi Kumagai, 2020, KDD.

Adaptive Data Pruning for Support Vector Machines

Naonori Ueda, Yasuhiro Fujiwara, Yasutoshi Ida, 2018, 2018 IEEE International Conference on Big Data (Big Data).

B308 On Input Design for Multi-variable System Identification

Shuichi Adachi, Sekitoshi Kanai, Hideo Muroi, 2015 .

Improving simultaneous head-related transfer function estimations via input design modification

Kentaro Matsui, Yasushige Nakayama, Shuichi Adachi, 2015 .

Autoencoding Binary Classifiers for Supervised Anomaly Detection pdf

Hiroshi Takahashi, Tomoharu Iwata, Masanori Yamada, 2019, PRICAI.

Constraining Logits by Bounded Function for Adversarial Robustness pdf

Hiroshi Takahashi, Yasutoshi Ida, Sekitoshi Kanai, 2020, 2021 International Joint Conference on Neural Networks (IJCNN).

Kentaro Matsui, Yasushige Nakayama, Shuichi Adachi, 2014 .

Preventing Gradient Explosions in Gated Recurrent Units

Yasuhiro Fujiwara, Sotetsu Iwamura, Sekitoshi Kanai, 2017, NIPS.

Fast and Accurate Anchor Graph-based Label Prediction

Naonori Ueda, Atsutoshi Kumagai, Yasutoshi Ida, 2021, CIKM.

Smoothness Analysis of Loss Functions of Adversarial Training pdf

Yasutoshi Ida, Sekitoshi Kanai, Masanori Yamada, 2021, ArXiv.

Fast Algorithm for Anchor Graph Hashing

Naonori Ueda, Atsutoshi Kumagai, Yasuhiro Fujiwara, 2021, Proc. VLDB Endow..

Image Enhanced Rotation Prediction for Self-Supervised Learning

Shin'ya Yamaguchi, Sekitoshi Kanai, Shoichiro Takeda, 2019, 2021 IEEE International Conference on Image Processing (ICIP).

Fast Similarity Computation for t-SNE

Naonori Ueda, Atsutoshi Kumagai, Yasuhiro Fujiwara, 2021, 2021 IEEE 37th International Conference on Data Engineering (ICDE).

Smoothness Analysis of Adversarial Training

Yasutoshi Ida, Sekitoshi Kanai, Masanori Yamada, 2021, 2103.01400.

Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression pdf

Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, 2021, ArXiv.

F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain pdf

Shin'ya Yamaguchi, Sekitoshi Kanai, Sekitoshi Kanai, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).