A new boosting algorithm ADABOOST-R for regression problems is presented and upper bound on the error is obtained. Experimental results to compare ADABOOST-R and other learning alg...
In this paper, we propose a new asymmetric boosting method, Boosting with Different Costs. Traditional boosting methods assume the same cost for misclassified instances from di...
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
Abstract. In this paper we upgrade linear logistic regression and boosting to multi-instance data, where each example consists of a labeled bag of instances. This is done by connec...
We address the problem of estimating human pose in video sequences, where rough location has been determined. We exploit both appearance and motion information by defining suitabl...