The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Several research areas today overlap between the tracks of databases, information retrieval and knowledge management, such as natural language processing, semantic web, digital li...
This paper presents a suite of methods and results for the semantic disambiguation of WordNet glosses. WordNet is a resource widely used in natural language processing and artific...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Machine learning algorithms in various forms are now increasingly being used on a variety of portable devices, starting from cell phones to PDAs. They often form a part of standard...