Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
We present a novel method to create perpetual animations from a small set of given keyframes. Existing approaches either are limited to re-sequencing large amounts of existing ima...
William Van Haevre, Fabian Di Fiore, Frank Van Ree...
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Abstract. Existing methods to text plagiarism analysis mainly base on “chunking”, a process of grouping a text into meaningful units each of which gets encoded by an integer nu...