The huge amount of the available information in the Web creates the need of effective information extraction systems that are able to produce metadata that satisfy user's inf...
The nature of the internet as a non-peer-reviewed (and more generally largely unregulated) publication medium has allowed wide-spread promotion of inaccurate and unproven medical ...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...