ダウンロード数: 108
このアイテムのファイル:
ファイル | 記述 | サイズ | フォーマット | |
---|---|---|---|---|
IJCAI 2015_4091.pdf | 1.17 MB | Adobe PDF | 見る/開く |
タイトル: | Instance-wise weighted nonnegative matrix factorization for aggregating partitions with locally reliable clusters |
著者: | Zheng, Xiaodong Zhu, Shanfeng Gao, Junning Mamitsuka, Hiroshi |
著者名の別形: | 馬見塚, 拓 |
発行日: | 25-Jul-2015 |
出版者: | AAAI Press |
誌名: | Proceedings of the 24th International Conference on Artificial Intelligence (IJCAI 15) |
開始ページ: | 4091 |
終了ページ: | 4097 |
抄録: | We address an ensemble clustering problem, where reliable clusters are locally embedded in given multiple partitions. We propose a new nonnegative matrix factorization (NMF)-based method, in which locally reliable clusters are explicitly considered by using instance-wise weights over clusters. Our method factorizes the input cluster assignment matrix into two matrices H and W, which are optimized by iteratively 1) updating H and W while keeping the weight matrix constant and 2) updating the weight matrix while keeping H and W constant, alternatively. The weights in the second step were updated by solving a convex problem, which makes our algorithm significantly faster than existing NMF-based ensemble clustering methods. We empirically proved that our method outperformed a lot of cutting-edge ensemble clustering methods by using a variety of datasets. |
記述: | IJCAI-15: Buenos Aires, Argentina, 25–31 July 2015 |
著作権等: | AAAI Press ©2015 This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 |
URI: | http://hdl.handle.net/2433/218488 |
関連リンク: | http://www.ijcai.org/Abstract/15/574 http://dl.acm.org/citation.cfm?id=2832747.2832819 |
出現コレクション: | 学術雑誌掲載論文等 |
このリポジトリに保管されているアイテムはすべて著作権により保護されています。