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KDD
2006
ACM
115views Data Mining» more  KDD 2006»
14 years 10 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
KDD
2005
ACM
160views Data Mining» more  KDD 2005»
14 years 10 months ago
Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering
Heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. While the co-clustering algorithms for two t...
Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, ...
KDD
2005
ACM
165views Data Mining» more  KDD 2005»
14 years 10 months ago
Co-clustering by block value decomposition
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
CHI
2004
ACM
14 years 10 months ago
Story lifecycle in a product development organization
This poster describes an integrated set of stories and story-based activities that we have used in product development in IBM Software Group's Lotus product organizations. We...
Majie Zeller, Sandra L. Kogan, Michael J. Muller, ...
POPL
2008
ACM
14 years 10 months ago
Imperative self-adjusting computation
Self-adjusting computation enables writing programs that can automatically and efficiently respond to changes to their data (e.g., inputs). The idea behind the approach is to stor...
Umut A. Acar, Amal Ahmed, Matthias Blume