Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
We present a demonstration of a newly developed text stream event detection method on over a million articles from the New York Times corpus. The event detection is designed to ope...
Tristan Snowsill, Ilias N. Flaounas, Tijl De Bie, ...
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
Latent Dirichlet allocation is a fully generative statistical language model that has been proven to be successful in capturing both the content and the topics of a corpus of docum...
Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
We present a tool for interactive exploration of graphs that integrates advanced graph mining methods in an interactive visualization framework. The tool enables efficient explorat...
The focus of this paper is a question answering system, where the answers are retrieved from a collection of textual documents. The system also includes automatic document summariz...
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...