岡嶋穣: NECの研究者

研究開発トップに戻る

2022年2月22日

岡嶋穣（Yuzuru Okajima）

研究分野

機械学習
大規模データ処理のためのアルゴリズム

学会発表

Yoichi Sasaki, Yuzuru Okajima, "Alternative Ruleset Discovery to Support Black-box Model Predictions", in Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM), December 7-10, 2021, Auckland, New Zealand.
Daniel Andrade, Yuzuru Okajima. Efficient Bayes Risk Estimation for Cost-Sensitive Classification. The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), 2019.
Yuzuru Okajima, Kunihiko Sadamasa. Decision List Optimization based on Continuous Relaxation. The SIAM International Conference on Data Mining (SDM19), 2019.
Yuzuru Okajima, Kunihiko Sadamasa. Deep neural networks constrained by decision rules. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), January, 2019
Yuzuru Okajima and Koichi Maruyama. Random Clustering for Multiple Sampling Units to Speed Up Run-time Sample Generation. DEIM 2018, 2018.
佐々木耀一, 木村圭吾, 山本風人, 岡嶋穣, 定政邦彦. 有向ハイパーグラフ上での到達可能性判定の高速化. 2018年度人工知能学会全国大会（第32回）, 2018.
佐々木耀一, 木村圭吾, 山本風人, 岡嶋穣, 定政邦彦. 有向ハイパーグラフ上の到達可能性判定問題に対するZDDを用いた効率的なアルゴリズム. 基盤(S) 離散構造処理系プロジェクト「2018年度初夏のワークショップ」, 2018.
Daniel Andrade, Kenji Fukumizu, and Yuzuru Okajima. Convex Feature Clustering and Selection With Class Label Information. Optimization for Machine Learning at NIPS 2017 Workshop, Long Beach, 2017.
Yuzuru Okajima, Kouichi Maruyama, “Faster Linear-space Orthogonal Range Searching in Arbitrary Dimensions”, Proceedings of the Meeting on Algorithm Engineering & Expermiments (ALENEX15)
Yuzuru Okajima, "Top-k substring matching for auto-completion", Proceedings of the Meeting on Algorithm Engineering & Expermiments (ALENEX14)

ジャーナル

Yuzuru Okajima, Koichi Maruyama. Random Clustering for Multiple Sampling Units to Speed Up Run-time Sample Generation. DBSJ Journal, Vol. 17, March, 2019.