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CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
14 years 3 months ago
Parameter estimation with expected and residual-at-risk criteria
In this paper we study a class of uncertain linear estimation problems in which the data are affected by random uncertainty. In this setting, we consider two estimation criteria,...
Giuseppe Carlo Calafiore, Ufuk Topcu, Laurent El G...
NIPS
2004
13 years 10 months ago
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 8 months ago
Robust Matrix Decomposition with Outliers
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...
Daniel Hsu, Sham M. Kakade, Tong Zhang
IJON
2007
184views more  IJON 2007»
13 years 8 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
BMVC
2010
13 years 6 months ago
TV-Based Multi-Label Image Segmentation with Label Cost Prior
This paper studies image segmentation based on the minimum description length (MDL) functional combining spatial regularization with a penality for the number of distinct segments...
Jing Yuan, Yuri Boykov