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ICDE
2009
IEEE
140views Database» more  ICDE 2009»
16 years 12 days ago
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
One of the most challenging aspects of managing a very large data warehouse is identifying how queries will behave before they start executing. Yet knowing their performance charac...
Archana Ganapathi, Harumi A. Kuno, Umeshwar Dayal,...
NIPS
2008
15 years 3 days ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
15 years 3 days ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
ILP
1999
Springer
15 years 2 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
LATIN
2010
Springer
15 years 5 months ago
Compact Rich-Functional Binary Relation Representations
Binary relations are an important abstraction arising in a number of data representation problems. Each existing data structure specializes in the few basic operations required by ...
Jérémy Barbay, Francisco Claude, Gon...