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» A Two-Level Approach to Making Class Predictions
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ICML
2004
IEEE
14 years 6 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
13 years 10 months ago
Combining partitions by probabilistic label aggregation
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
Tilman Lange, Joachim M. Buhmann
SIGIR
2008
ACM
13 years 5 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 5 months ago
Empirical comparisons of various voting methods in bagging
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
Kelvin T. Leung, Douglas Stott Parker Jr.
IWMM
2009
Springer
164views Hardware» more  IWMM 2009»
13 years 12 months ago
Live heap space analysis for languages with garbage collection
The peak heap consumption of a program is the maximum size of the live data on the heap during the execution of the program, i.e., the minimum amount of heap space needed to run t...
Elvira Albert, Samir Genaim, Miguel Gómez-Z...