2つの「2つのオブジェクトの選好の差」の大小関係を比較したデータを用いることで、より詳細な順序付けを学習する手法を提案した論文が、データ科学分野の国際会議 IEEE International Conference on Data Science and Advanced Analytics (DSAA) に採択されました。
Guoxi Zhang, Jiyi Li, Hisashi Kashima.
Improving Pairwise Rank Aggregation via Querying for Rank Difference.
In Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2022.
Ryoma Sato.
Towards Principled User-side Recommender Systems.
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
# ユーザーサイドの推薦システムの理論的な実現可能性を示し、望ましい性質をもつユーザーサイドの推薦アルゴリズムを提案
Ryoma Sato.
CLEAR: A Fully User-side Image Search System.
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
# ユーザーが設定したスコア関数を元に画像検索を行うブラウザで動作するデモを公開
Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling.
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
# 「双子論文」に基づく因果推論を用いた研究インパクトの分析手法を提案
機械学習・データマイニングの国際会議である European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) に二本の論文が採択されました：
Guoxi Zhang, Hisashi Kashima.
Batch Reinforcement Learning from Crowds.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022.
Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada.
Feature Robust Optimal Transport for High-dimensional Data.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022.
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuuki Yamanaka, Hisashi Kashima.
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders.
In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima. Mitigating Observation Biases in Crowdsourced Label Aggregation. In Proceedings of the 26th International Conference on Pattern Recognition (ICPR), 2022.
Yoichi Chikahara, Makoto Yamada, Hisashi Kashima. Feature Selection for Discovering Distributional Treatment Effect Modifiers. In Proceedings of the 38th Conference on Uncertaintly in Artificial Intelligence (UAI), 2022.
適切に正規化することで、単純なbag-of-words が Word Mover’s Distance に迫る性能を発揮できることを提案した論文が、機械学習の国際会議 ICML に採択されました。
Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Re-evaluating Word Mover's Distance.
In Proceedings of the 39th International Conference on Machine Learning (ICML), 2022.
Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada Fixed Support Tree-Sliced Wasserstein Barycenter In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) # 超高速なBarycenter推定手法の提案
Benjamin Poignard, Peter Naylor, Héctor Climente, Makoto Yamada Feature Screening with Kernel Knockoff In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) # カーネル法とKnockoff filterに基づいた選択的推論の提案
Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima. Learning Time-series Shapelets Enhancing Discriminability. In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022. # 時系列のクラス分類に貢献するShapelet（部分時系列）特徴量を学習する手法を提案
eラーニング上の生徒の習熟度を特徴量構造の発見によって推定する手法を提案した論文がAAAI Symposium on Educational Advances in Artificial Intelligence (EAAI)に採択されました：
Sein Minn, Jill-Jenn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu. Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. In Proceedings of the 12th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI), 2022.
