RANSAC (Random Sample Consensus) is a popular and effective technique for estimating model parameters in the presence of outliers. Efficient algorithms are necessary for both fram...
Paul McIlroy, Edward Rosten, Simon Taylor, Tom Dru...
In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem ...
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
Abstract. Variational frameworks based on level set methods are popular for the general problem of image segmentation. They combine different feature channels in an energy minimiz...