290 search results - page 25 / 58 » A Randomized Algorithm for Large Scale Support Vector Learni... |
NECO
2008
13 years 8 months ago
2008
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
MICCAI
2010
Springer
13 years 6 months ago
2010
Springer
We address a novel problem domain in the analysis of optical coherence tomography (OCT) images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to ...
KDD
2004
ACM
14 years 8 months ago
2004
ACM
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
CEC
2009
IEEE
14 years 3 months ago
2009
IEEE
— In this paper, we propose a new algorithm, named JACC-G, for large scale optimization problems. The motivation is to improve our previous work on grouping and adaptive weightin...
AAAI
2008
13 years 10 months ago
2008
Most standard learning algorithms, such as Logistic Regression (LR) and the Support Vector Machine (SVM), are designed to deal with i.i.d. (independent and identically distributed...