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» Generalization Bounds for Learning Kernels
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NIPS
2004
13 years 11 months ago
Maximum-Margin Matrix Factorization
We present a novel approach to collaborative prediction, using low-norm instead of low-rank factorizations. The approach is inspired by, and has strong connections to, large-margi...
Nathan Srebro, Jason D. M. Rennie, Tommi Jaakkola
COLT
2005
Springer
14 years 3 months ago
A New Perspective on an Old Perceptron Algorithm
Abstract. We present a generalization of the Perceptron algorithm. The new algorithm performs a Perceptron-style update whenever the margin of an example is smaller than a predefi...
Shai Shalev-Shwartz, Yoram Singer
COLT
2000
Springer
14 years 1 months ago
Leveraging for Regression
In this paper we examine master regression algorithms that leverage base regressors by iteratively calling them on modified samples. The most successful leveraging algorithm for c...
Nigel Duffy, David P. Helmbold
WCE
2007
13 years 11 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
NIPS
2001
13 years 11 months ago
Quantizing Density Estimators
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
Peter Meinicke, Helge Ritter