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» Algorithmic randomness of continuous functions
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ICML
2008
IEEE
14 years 9 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
CVPR
2010
IEEE
14 years 4 months ago
A Diffusion Approach to Seeded Image Segmentation
Seeded image segmentation is a popular type of supervised image segmentation in computer vision and image processing. Previous methods of seeded image segmentation treat the image...
Juyong Zhang, Jianmin Zheng, Jianfei Cai
CRYPTO
2007
Springer
132views Cryptology» more  CRYPTO 2007»
14 years 2 months ago
How Should We Solve Search Problems Privately?
Abstract. Secure multiparty computation allows a group of distrusting parties to jointly compute a (possibly randomized) function of their inputs. However, it is often the case tha...
Amos Beimel, Tal Malkin, Kobbi Nissim, Enav Weinre...
ENC
2005
IEEE
14 years 2 months ago
Saving Evaluations in Differential Evolution for Constrained Optimization
Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
Efrén Mezura-Montes, Carlos A. Coello Coell...
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
14 years 14 days ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo