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...
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources -from sensor data, experimental data, data fro...
Abstract—Network coding is emerging as a promising alternative to traditional content distribution approaches in P2P networks. By allowing information mixture in peers, it simpli...
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
The quality of a local search engine, such as Google and Bing Maps, heavily relies on its geographic datasets. Typically, these datasets are obtained from multiple sources, e.g., ...