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SLSFS
2005
Springer
15 years 9 months ago
Random Projection, Margins, Kernels, and Feature-Selection
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Avrim Blum
ICML
2005
IEEE
16 years 5 months ago
Multi-class protein fold recognition using adaptive codes
We develop a novel multi-class classification method based on output codes for the problem of classifying a sequence of amino acids into one of many known protein structural class...
Eugene Ie, Jason Weston, William Stafford Noble, C...
ICML
2003
IEEE
16 years 5 months ago
An Analysis of Rule Evaluation Metrics
In this paper we analyze the most popular evaluation metrics for separate-and-conquer rule learning algorithms. Our results show that all commonly used heuristics, including accur...
Johannes Fürnkranz, Peter A. Flach
ICML
2001
IEEE
16 years 5 months ago
Expectation Maximization for Weakly Labeled Data
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
Yuri A. Ivanov, Bruce Blumberg, Alex Pentland
ICML
2008
IEEE
16 years 5 months ago
The projectron: a bounded kernel-based Perceptron
We present a discriminative online algorithm with a bounded memory growth, which is based on the kernel-based Perceptron. Generally, the required memory of the kernelbased Percept...
Francesco Orabona, Joseph Keshet, Barbara Caputo