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» Using Machine Learning to Focus Iterative Optimization
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AAAI
2007
15 years 5 months ago
Clustering with Local and Global Regularization
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
Fei Wang, Changshui Zhang, Tao Li
ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
15 years 9 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 7 months ago
On the appropriateness of evolutionary rule learning algorithms for malware detection
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
ECCV
2004
Springer
16 years 5 months ago
User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior
When we take a picture through transparent glass the image we obtain is often a linear superposition of two images: the image of the scene beyond the glass plus the image of the sc...
Anat Levin, Yair Weiss
WWW
2011
ACM
14 years 10 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...