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Y. Ida, S. Kanai, A. Kumagai, T. Iwata, Y. Fujiwara,
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,
Neural Information Processing Systems (NeurIPS), 2024, to appear.
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Y. Fujiwara, A. Kumagai, Y. Ida, M. Nakano, M. Nakatsuji, A. Kimura,
Efficient Algorithm for K-Multiple-Means,
Special Interest Group on Management of Data (SIGMOD), 2024, to appear.
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S. Kanai, S. Yamaguchi, M. Yamada, H. Takahashi, K. Ohno, Y. Ida,
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training,
International Conference on Machine Learning (ICML), 2023.
[paper]
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Y. Ida, S. Kanai, A. Kumagai,
Fast Block Coordinate Descent for Non-Convex Group Regularizations,
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.
[paper]
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Y. Fujiwara, Y. Ida, A. Kumagai, M. Nakano, A. Kimura, N. Ueda
Efficient Network Representation Learning via Cluster Similarity,
International Conference on Database Systems for Advanced Applications (DASFAA), 2023.
[paper]
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Y. Ida, S. Kanai, K. Adachi, A. Kumagai, Y. Fujiwara,
Fast Regularized Discrete Optimal Transport with Group-sparse Regularizers,
Association for the Advancement of Artificial Intelligence (AAAI), 2023.
[preprint]
[slide]
[poster]
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K. Ohno, S. Kanai, Y. Ida,
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks,
Association for the Advancement of Artificial Intelligence (AAAI), 2023.
[preprint]
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Y. Fujiwara, M. Nakano, A.Kumagai, Y. Ida, A. Kimura, N. Ueda,
Fast Binary Network Hashing via Graph Clustering,
IEEE BigData, 2022.
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A. Kumagai, T. Iwata, Y. Ida, Y. Fujiwara,
Meta-learning for Feature Selection with Hilbert-Schmidt Independence Criterion,
Neural Information Processing Systems (NeurIPS), 2022.
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D. Chijiwa, S. Yamaguchi, A. Kumagai, Y. Ida,
Meta-ticket: Finding Optimal Subnetworks for Few-shot Learning within Randomly Initialized Neural Networks,
Neural Information Processing Systems (NeurIPS), 2022.
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Y, Fujiwara, Y. Ida, A. Kumagai, S. Kanai, N. Ueda,
Fast and Accurate Anchor Graph-based Label Prediction,
International Conference on Information and Knowledge Management (CIKM), 2021.
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D. Chijiwa, S. Yamaguchi, Y. Ida, K. Umakoshi, T. Inoue,
Pruning Randomly Initialized Neural Networks with Iterative Randomization,
Neural Information Processing Systems (NeurIPS, spotlight), 2021.
[paper]
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S. Kanai, M. Yamada, S. Yamaguchi, H. Takahashi, Y. Ida,
Constraining Logits by Bounded Function for Adversarial Robustness,
International Joint Conference on Neural Networks (IJCNN), 2021.
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Y. Fujiwara, Y. Ida, S, Kanai, A. Kumagai, N. Ueda,
Fast Similarity Computation for t-SNE,
IEEE International Conference on Data Engineering (ICDE), 2021.
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Y. Ida, S. Kanai, Y. Fujiwara, T. Iwata, K. Takeuchi, H. Kashima,
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance,
International Conference on Machine Learning (ICML), 2020.
[paper]
[slide]
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Y. Fujiwara, A. Kumagai, S. Kanai, Y. Ida, T. Kawanishi, N. Ueda
Efficient Algorithm for the b-Matching Graph,
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020.
[paper]
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Y. Ida, Y. Fujiwara,
Improving Generalization Performance of Adaptive Learning Rate by Switching from Block Diagonal Matrix Preconditioning to SGD,
International Joint Conference on Neural Networks (IJCNN), 2020.
[paper]
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S. Kanai, Y. Ida, Y. Fujiwara, M. Yamada, S. Adachi,
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks,
Association for the Advancement of Artificial Intelligence (AAAI), 2020.
[paper(pdf)]
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Y. Ida, Y. Fujiwara, H. Kashima,
Fast Sparse Group Lasso,
Neural Information Processing Systems (NeurIPS), 2019.
[paper]
[slide]
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Y. Fujiwara, Y. Ida, S. Kanai, A. Kumagai, J. Arai, N. Ueda,
Fast Random Forest Algorithm via Incremental Upper Bound,
International Conference on Information and Knowledge Management (CIKM), 2019.
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Y. Fujiwara, S. Kanai, J. Arai, Y. Ida, N. Ueda,
Efficient Data Point Pruning for One-Class SVM,
Association for the Advancement of Artificial Intelligence (AAAI), 2019.
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Y. Ida, Y. Fujiwara,
Network Implosion: Effective Model Compression for ResNets via Static Layer Pruning and Retraining,
International Joint Conference on Neural Networks (IJCNN), 2019.
[paper]
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Y. Fujiwara, J. Arai, S. Kanai, Y. Ida, N. Ueda,
Adaptive Data Pruning for Support Vector Machines,
IEEE BigData, 2018.
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Y. Ida, Y. Fujiwara, S. Iwamura,
Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks,
International Joint Conference on Artificial Intelligence (IJCAI), 2017.
[paper]
[slide]
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Y. Fujiwara, Y. Ida, H. Shiokawa, S. Iwamura,
Fast Lasso Algorithm via Selective Coordinate Descent,
Association for the Advancement of Artificial Intelligence (AAAI), 2016.
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Y. Fujiwara, M. Nakatsuji, Y. Ida, M. Toyoda,
Adaptive Message Update for Fast Affinity Propagation,
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016.
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Y. Ida, T. Nakamura, T. Matsumoto,
Domain-Dependent/Independent Topic Switching Model for Online Reviews with Numerical Ratings,
ACM International Conference on Information and Knowledge Management (CIKM), 2013.
[paper]
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H. Miyashita, T. Suzuki, T. Nakamura, Y. Ida, Takashi Matsumoto, T. Kaburagi
Nonparametric Bayes-based Heterogeneous "Drosophila melanogaster" Gene Regulatory Network Inference: T-Process Regression,
Artificial Intelligence and Applications (AIA), 2013. Best Student Paper Award.
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T. Suzuki, T. Nakamura, Y. Ida, T. Matsumoto
Handling Incomplete Matrix Data Via Continuous-Valued Infinite Relational Model,
International Conference on Acoustic, Speech, and Signal Processing (ICASSP), 2012.