95 search results - page 9 / 19 » Reduction Techniques for Instance-Based Learning Algorithms |
FOCS
2005
IEEE
15 years 3 months ago
2005
IEEE
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
NPL
1998
14 years 9 months ago
1998
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
ICCV
2007
IEEE
15 years 3 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
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CCGRID
2007
IEEE
15 years 3 months ago
2007
IEEE
Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closel...