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» Generalized Boosting Algorithms for Convex Optimization
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CVPR
2008
IEEE
14 years 2 months ago
Scene understanding with discriminative structured prediction
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
Jinhui Yuan, Jianmin Li, Bo Zhang
JMLR
2010
169views more  JMLR 2010»
13 years 2 months ago
Consensus-Based Distributed Support Vector Machines
This paper develops algorithms to train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
ICCV
2009
IEEE
15 years 16 days ago
A Global Perspective on MAP Inference for Low-Level Vision
In recent years the Markov Random Field (MRF) has become the de facto probabilistic model for low-level vision applications. However, in a maximum a posteriori (MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
MP
2006
142views more  MP 2006»
13 years 7 months ago
Exploring the Relationship Between Max-Cut and Stable Set Relaxations
The max-cut and stable set problems are two fundamental NP-hard problems in combinatorial optimization. It has been known for a long time that any instance of the stable set probl...
Monia Giandomenico, Adam N. Letchford
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
13 years 11 months ago
Convergence to global optima for genetic programming systems with dynamically scaled operators
This work shows asymptotic convergence to global optima for a family of dynamically scaled genetic programming systems where the underlying population consists of a fixed number o...
Lothar M. Schmitt, Stefan Droste