We present MBoost, a novel extension to AdaBoost that extends boosting to use multiple weak learners explicitly, and provides robustness to learning models that overfit or are po...
We present an extension to a recent method for learning of nonlinear manifolds, which allows to incorporate general cost functions. We focus on the -insensitive loss and visually d...
We present a novel extension to a recently proposed incremental learning algorithm for the word segmentation problem originally introduced in Goldwater (2006). By adding rejuvenat...
In this paper, we propose a two-dimensional active learning scheme and show its application in image classification. Traditional active learning methods select samples only along ...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...