How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
Comparative evaluation of Machine Learning (ML) systems used for Information Extraction (IE) has suffered from various inconsistencies in experimental procedures. This paper repor...
Neil Ireson, Fabio Ciravegna, Mary Elaine Califf, ...
A significant challenge in developing planning systems for practical applications is the difficulty of acquiring the domain knowledge needed by such systems. One method for acquir...
We develop a novel multi-class classification method based on output codes for the problem of classifying a sequence of amino acids into one of many known protein structural class...
Eugene Ie, Jason Weston, William Stafford Noble, C...
A geometric construction is presented which is shown to be an effective tool for understanding and implementing multi-category support vector classification. It is demonstrated ho...
We apply classic online learning techniques similar to the perceptron algorithm to the problem of learning a function defined on a graph. The benefit of our approach includes simp...
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
We present a new method to estimate the intrinsic dimensionality of a submanifold M in Rd from random samples. The method is based on the convergence rates of a certain U-statisti...
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...