We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
We present a static index pruning method, to be used in ad-hoc document retrieval tasks, that follows a documentcentric approach to decide whether a posting for a given term shoul...
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
A novel framework for providing probabilistically-bounded approximate answers to non-holistic aggregate range queries in OLAP is presented in this paper. Such a framework allows u...
Automatically translating natural language into machine-readable instructions is one of major interesting and challenging tasks in Natural Language (NL) Processing. This problem c...