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» The Random Subspace Method for Constructing Decision Forests
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CVPR
2008
IEEE
14 years 7 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
SADM
2010
128views more  SADM 2010»
13 years 4 months ago
Online training on a budget of support vector machines using twin prototypes
: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...
Zhuang Wang, Slobodan Vucetic
SAS
2004
Springer
140views Formal Methods» more  SAS 2004»
13 years 11 months ago
Path-Sensitive Analysis for Linear Arithmetic and Uninterpreted Functions
We describe data structures and algorithms for performing a path-sensitive program analysis to discover equivalences of expressions involving linear arithmetic or uninterpreted fun...
Sumit Gulwani, George C. Necula
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
13 years 10 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen