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» Dimension Reduction for Supervised Ordering
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NIPS
2007
13 years 8 months ago
A general agnostic active learning algorithm
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni
CDC
2009
IEEE
185views Control Systems» more  CDC 2009»
14 years 3 days ago
Discrete Empirical Interpolation for nonlinear model reduction
A dimension reduction method called Discrete Empirical Interpolation (DEIM) is proposed and shown to dramatically reduce the computational complexity of the popular Proper Orthogo...
Saifon Chaturantabut, Danny C. Sorensen
SISAP
2008
IEEE
188views Data Mining» more  SISAP 2008»
14 years 1 months ago
High-Dimensional Similarity Retrieval Using Dimensional Choice
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...
Dave Tahmoush, Hanan Samet
WSCG
2001
75views more  WSCG 2001»
13 years 8 months ago
Towards Mechanical Level of Detail for Knitwear Simulation
This paper introduces the foundations of a new mechanical level of detail method dedicated to knitted fabric simulation. This method consists as a reduction of the knitted cloth p...
Olivier Nocent, Jean-Michel Nourrit, Yannick R&eac...
JCNS
2010
100views more  JCNS 2010»
13 years 5 months ago
Morphologically accurate reduced order modeling of spiking neurons
Accurately simulating neurons with realistic morphological structure and synaptic inputs requires the solution of large systems of nonlinear ordinary differential equations. We ap...
Anthony R. Kellems, Saifon Chaturantabut, Danny C....