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» Convex optimization for the design of learning machines
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ACML
2009
Springer
14 years 1 months ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Yuhong Guo
ICML
2008
IEEE
14 years 10 months ago
Efficiently solving convex relaxations for MAP estimation
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
M. Pawan Kumar, Philip H. S. Torr
ICML
2009
IEEE
14 years 10 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
Chun-Nam John Yu, Thorsten Joachims
ECML
2007
Springer
14 years 3 months ago
Discriminative Sequence Labeling by Z-Score Optimization
Abstract. We consider a new discriminative learning approach to sequence labeling based on the statistical concept of the Z-score. Given a training set of pairs of hidden-observed ...
Elisa Ricci, Tijl De Bie, Nello Cristianini
EMMCVPR
2005
Springer
14 years 2 months ago
Reverse-Convex Programming for Sparse Image Codes
Abstract. Reverse-convex programming (RCP) concerns global optimization of a specific class of non-convex optimization problems. We show that a recently proposed model for sparse ...
Matthias Heiler, Christoph Schnörr