Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
— Emerging uncertain database applications often involve the cleansing (conditioning) of uncertain databases using additional information as new evidence for reducing the uncerta...
The construction and maintenance of data warehouses (views) in large-scale environments composed of numerous distributed and evolving information sources (ISs) such as the WWW has ...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...