The paper extends the notion of linear programming boosting to handle uneven datasets. Extensive experiments with text classification problem compare the performance of a number o...
We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...