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NIPS
2007
13 years 10 months ago
Predictive Matrix-Variate t Models
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
Shenghuo Zhu, Kai Yu, Yihong Gong
DCG
1998
80views more  DCG 1998»
13 years 8 months ago
Fitting a Set of Points by a Circle
Given a set of points S = fp1; : : : ; png in Euclidean d-dimensional space, we address the problem of computing the d-dimensional annulus of smallest width containing the set. We...
Jesus Garcia-Lopez, Pedro A. Ramos, Jack Snoeyink
CVPR
2008
IEEE
14 years 11 months ago
A polynomial-time bound for matching and registration with outliers
We present a framework for computing optimal transformations, aligning one point set to another, in the presence of outliers. Example applications include shape matching and regis...
Carl Olsson, Olof Enqvist, Fredrik Kahl
PAMI
2011
13 years 4 months ago
Cost-Sensitive Boosting
—A novel framework is proposed for the design of cost-sensitive boosting algorithms. The framework is based on the identification of two necessary conditions for optimal cost-sen...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
JMLR
2010
121views more  JMLR 2010»
13 years 4 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor