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» Introduction to Randomized Algorithms
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ECAI
2008
Springer
15 years 8 months ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo
333
Voted

Book
19360views
17 years 5 months ago
Numerical Recipes in C
C code implementation of several math algorithms such as Linear Algebraic Equations, Interpolation and Extrapolation, Integration of Functions, Evaluation of Functions, Random Num...
William H. Press, Saul A. Teukolsky, William T. Ve...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
16 years 7 months ago
The offset tree for learning with partial labels
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Alina Beygelzimer, John Langford
CHI
2002
ACM
16 years 6 months ago
Gaze behavior of talking faces makes a difference
We present the results of an experiment investigating the effects of a talking head's gaze behavior on the user's quality assessment of the interface. We compared a vers...
Ivo van Es, Dirk Heylen, Betsy van Dijk, Anton Nij...
151
Voted
STOC
2001
ACM
140views Algorithms» more  STOC 2001»
16 years 6 months ago
Compatible sequences and a slow Winkler percolation
Two infinite 0-1 sequences are called compatible when it is possible to cast out 0's from both in such a way that they become complementary to each other. Answering a question...
Péter Gács