74 search results - page 4 / 15 » Robust bounds for classification via selective sampling |
NIPS
2004
13 years 7 months ago
2004
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
KDD
2008
ACM
14 years 6 months ago
2008
ACM
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
JMLR
2002
13 years 5 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
CORR
2002
Springer
13 years 5 months ago
2002
Springer
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
ICDM
2007
IEEE
13 years 9 months ago
2007
IEEE
The problem of selecting a sample subset sufficient to preserve diversity arises in many applications. One example is in the design of recombinant inbred lines (RIL) for genetic a...