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JCNS
2010
104views more  JCNS 2010»
13 years 7 months ago
A new look at state-space models for neural data
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
CCE
2006
13 years 9 months ago
An efficient algorithm for large scale stochastic nonlinear programming problems
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
Y. Shastri, Urmila M. Diwekar
CGF
2011
13 years 19 days ago
Intrinsic Shape Matching by Planned Landmark Sampling
Recently, the problem of intrinsic shape matching has received a lot of attention. A number of algorithms have been proposed, among which random-sampling-based techniques have bee...
Art Tevs, Alexander Berner, Michael Wand, Ivo Ihrk...
SADM
2010
128views more  SADM 2010»
13 years 7 months ago
Online training on a budget of support vector machines using twin prototypes
: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...
Zhuang Wang, Slobodan Vucetic
ACIVS
2008
Springer
13 years 11 months ago
Motion Recovery for Uncalibrated Turntable Sequences Using Silhouettes and a Single Point
Abstract. This paper addresses the problem of self-calibration and motion recovery for turntable sequences. Previous works exploited silhouette correspondences induced by epipolar ...
Hui Zhang, Ling Shao, Kwan-Yee Kenneth Wong