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» Machine Learning by Function Decomposition
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ICML
2010
IEEE
15 years 2 months ago
Multi-Class Pegasos on a Budget
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Zhuang Wang, Koby Crammer, Slobodan Vucetic
JMLR
2010
108views more  JMLR 2010»
14 years 8 months ago
WEKA - Experiences with a Java Open-Source Project
WEKA is a popular machine learning workbench with a development life of nearly two decades. This article provides an overview of the factors that we believe to be important to its...
Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geof...
NIPS
2001
15 years 3 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
ICML
2000
IEEE
16 years 2 months ago
A Nonparametric Approach to Noisy and Costly Optimization
This paper describes Pairwise Bisection: a nonparametric approach to optimizing a noisy function with few function evaluations. The algorithm uses nonparametric reasoning about si...
Brigham S. Anderson, Andrew W. Moore, David Cohn
ICML
2007
IEEE
16 years 2 months ago
Adaptive mesh compression in 3D computer graphics using multiscale manifold learning
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...
Sridhar Mahadevan