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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 9 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 9 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 9 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
STOC
2005
ACM
129views Algorithms» more  STOC 2005»
14 years 9 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
SIGMOD
2009
ACM
201views Database» more  SIGMOD 2009»
14 years 9 months ago
Cost based plan selection for xpath
We present a complete XPath cost-based optimization and execution framework and demonstrate its effectiveness and efficiency for a variety of queries and datasets. The framework i...
Haris Georgiadis, Minas Charalambides, Vasilis Vas...