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NIPS
2008
13 years 10 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
TIP
2008
168views more  TIP 2008»
13 years 8 months ago
A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution
Abstract--In this paper, we present a complete and practical algorithm for the approximation of level-set-based curve evolution suitable for real-time implementation. In particular...
Yonggang Shi, William Clement Karl
CVPR
2009
IEEE
15 years 3 months ago
Increased Discrimination in Level Set Methods with Embedded Conditional Random Fields
We propose a novel approach for improving level set seg- mentation methods by embedding the potential functions from a discriminatively trained conditional random field (CRF) in...
Dana Cobzas (University of Alberta), Mark Schmidt ...
ICPR
2008
IEEE
14 years 3 months ago
A least square kernel machine with box constraints
In this paper, we present a least square kernel machine with box constraints (LSKMBC). The existing least square machines assume Gaussian hyperpriors and subsequently express the ...
Jayanta Basak
MP
2011
12 years 11 months ago
Implicit solution function of P0 and Z matrix linear complementarity constraints
Abstract. Using the least element solution of the P0 and Z matrix linear complementarity problem (LCP), we define an implicit solution function for linear complementarity constrai...
Xiaojun Chen, Shuhuang Xiang