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ORCIDSekitoshi Kanai
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2020 – today
- 2024
[j2]Sekitoshi Kanai
, Masanori Yamada, Hiroshi Takahashi, Yuki Yamanaka, Yasutoshi Ida:
Relationship Between Nonsmoothness in Adversarial Training, Constraints of Attacks, and Flatness in the Input Space. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10817-10831 (2024)- [c24]Shin'ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa:
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks. CVPR 2024: 23481-23490 - [i17]Shin'ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa:
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks. CoRR abs/2403.10097 (2024) - [i16]Sekitoshi Kanai, Yasutoshi Ida, Kazuki Adachi, Mihiro Uchida, Tsukasa Yoshida, Shin'ya Yamaguchi:
Evaluating Time-Series Training Dataset through Lens of Spectrum in Deep State Space Models. CoRR abs/2408.16261 (2024) - 2023
- [c23]Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi, Atsutoshi Kumagai, Yasuhiro Fujiwara:
Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers. AAAI 2023: 7980-7987 - [c22]Kentaro Ohno, Sekitoshi Kanai, Yasutoshi Ida:
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks. AAAI 2023: 9319-9326 - [c21]Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai:
Fast Block Coordinate Descent for Non-Convex Group Regularizations. AISTATS 2023: 2481-2493 - [c20]Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Sekitoshi Kanai, Naoki Makishima, Atsushi Ando, Ryo Masumura:
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff. ICCV 2023: 4367-4378 - [c19]Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Kentaro Ohno, Yasutoshi Ida:
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training. ICML 2023: 15669-15695 - [c18]Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima:
Regularizing Neural Networks with Meta-Learning Generative Models. NeurIPS 2023 - [i15]Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi, Atsutoshi Kumagai, Yasuhiro Fujiwara:
Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers. CoRR abs/2303.07597 (2023) - [i14]Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima:
Regularizing Neural Networks with Meta-Learning Generative Models. CoRR abs/2307.13899 (2023) - [i13]Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Sekitoshi Kanai, Naoki Makishima, Atsushi Ando, Ryo Masumura:
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff. CoRR abs/2308.16454 (2023) - 2022
- [c17]Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima:
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. KDD 2022: 1739-1748 - [i12]Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima:
Transfer Learning with Pre-trained Conditional Generative Models. CoRR abs/2204.12833 (2022) - [i11]Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Yasutoshi Ida:
Switching One-Versus-the-Rest Loss to Increase the Margin of Logits for Adversarial Robustness. CoRR abs/2207.10283 (2022) - [i10]Kentaro Ohno, Sekitoshi Kanai, Yasutoshi Ida:
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks. CoRR abs/2210.01348 (2022) - 2021
- [j1]Yasuhiro Fujiwara, Sekitoshi Kanai, Yasutoshi Ida, Atsutoshi Kumagai, Naonori Ueda:
Fast Algorithm for Anchor Graph Hashing. Proc. VLDB Endow. 14(6): 916-928 (2021) - [c16]Yasuhiro Fujiwara, Yasutoshi Ida, Atsutoshi Kumagai, Sekitoshi Kanai, Naonori Ueda:
Fast and Accurate Anchor Graph-based Label Prediction. CIKM 2021: 504-513 - [c15]Shin'ya Yamaguchi, Sekitoshi Kanai:
F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain. ICCV 2021: 6723-6731 - [c14]Yasuhiro Fujiwara, Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Naonori Ueda:
Fast Similarity Computation for t-SNE. ICDE 2021: 1691-1702 - [c13]Shin'ya Yamaguchi, Sekitoshi Kanai, Tetsuya Shioda, Shoichiro Takeda:
Image Enhanced Rotation Prediction for Self-Supervised Learning. ICIP 2021: 489-493 - [c12]Sekitoshi Kanai, Masanori Yamada, Shin'ya Yamaguchi, Hiroshi Takahashi, Yasutoshi Ida:
Constraining Logits by Bounded Function for Adversarial Robustness. IJCNN 2021: 1-8 - [c11]Toshiaki Wakatsuki, Sekitoshi Kanai, Yasuhiro Fujiwara:
Accelerate Inference of CNNs for Video Analysis While Preserving Exactness Exploiting Activation Sparsity. MLSys 2021 - [i9]Masanori Yamada, Sekitoshi Kanai, Tomoharu Iwata, Tomokatsu Takahashi, Yuki Yamanaka, Hiroshi Takahashi, Atsutoshi Kumagai:
Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression. CoRR abs/2102.02950 (2021) - [i8]Sekitoshi Kanai, Masanori Yamada, Hiroshi Takahashi, Yuki Yamanaka, Yasutoshi Ida:
Smoothness Analysis of Loss Functions of Adversarial Training. CoRR abs/2103.01400 (2021) - [i7]Shin'ya Yamaguchi, Sekitoshi Kanai:
F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain. CoRR abs/2106.02343 (2021) - 2020
- [c10]Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara, Masanori Yamada, Shuichi Adachi:
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks. AAAI 2020: 4394-4403 - [c9]Shin'ya Yamaguchi, Sekitoshi Kanai, Takeharu Eda:
Effective Data Augmentation with Multi-Domain Learning GANs. AAAI 2020: 6566-6574 - [c8]Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima:
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. ICML 2020: 4594-4603 - [c7]Yasuhiro Fujiwara, Atsutoshi Kumagai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda:
Efficient Algorithm for the b-Matching Graph. KDD 2020: 187-197 - [i6]Sekitoshi Kanai, Masanori Yamada, Shin'ya Yamaguchi, Hiroshi Takahashi, Yasutoshi Ida:
Constraining Logits by Bounded Function for Adversarial Robustness. CoRR abs/2010.02558 (2020)
2010 – 2019
- 2019
- [c6]Yasuhiro Fujiwara, Sekitoshi Kanai, Junya Arai, Yasutoshi Ida, Naonori Ueda:
Efficient Data Point Pruning for One-Class SVM. AAAI 2019: 3590-3597 - [c5]Yasuhiro Fujiwara, Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Junya Arai, Naonori Ueda:
Fast Random Forest Algorithm via Incremental Upper Bound. CIKM 2019: 2205-2208 - [c4]Yuki Yamanaka, Tomoharu Iwata, Hiroshi Takahashi, Masanori Yamada, Sekitoshi Kanai:
Autoencoding Binary Classifiers for Supervised Anomaly Detection. PRICAI (2) 2019: 647-659 - [i5]Yuki Yamanaka, Tomoharu Iwata, Hiroshi Takahashi, Masanori Yamada, Sekitoshi Kanai:
Autoencoding Binary Classifiers for Supervised Anomaly Detection. CoRR abs/1903.10709 (2019) - [i4]Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara, Masanori Yamada, Shuichi Adachi:
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks. CoRR abs/1909.08830 (2019) - [i3]Shin'ya Yamaguchi, Sekitoshi Kanai, Takeharu Eda:
Effective Data Augmentation with Multi-Domain Learning GANs. CoRR abs/1912.11597 (2019) - [i2]Shin'ya Yamaguchi, Sekitoshi Kanai, Tetsuya Shioda, Shoichiro Takeda:
Multiple Pretext-Task for Self-Supervised Learning via Mixing Multiple Image Transformations. CoRR abs/1912.11603 (2019) - 2018
- [c3]Yasuhiro Fujiwara, Junya Arai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda:
Adaptive Data Pruning for Support Vector Machines. IEEE BigData 2018: 683-692 - [c2]Sekitoshi Kanai, Yasuhiro Fujiwara, Yuki Yamanaka, Shuichi Adachi:
Sigsoftmax: Reanalysis of the Softmax Bottleneck. NeurIPS 2018: 284-294 - [i1]Sekitoshi Kanai, Yasuhiro Fujiwara, Yuki Yamanaka, Shuichi Adachi:
Sigsoftmax: Reanalysis of the Softmax Bottleneck. CoRR abs/1805.10829 (2018) - 2017
- [c1]Sekitoshi Kanai, Yasuhiro Fujiwara, Sotetsu Iwamura:
Preventing Gradient Explosions in Gated Recurrent Units. NIPS 2017: 435-444
Coauthor Index
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