—Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compr...
We present a novel approach to integrate transliteration into Hindi-to-Urdu statistical machine translation. We propose two probabilistic models, based on conditional and joint pr...
Nadir Durrani, Hassan Sajjad, Alexander Fraser, He...
Most tracking algorithms implicitly apply a coarse segmentation of each target object using a simple mask such as a rectangle or an ellipse. Although convenient, such coarse segme...
In this paper, the feasibility of using finite totally ordered probability models under Aleliunas’s Theory of Probabilistic Logic [Aleliunas, 1988] is investigated. The general...
We revisit the idea of history-based parsing, and present a history-based parsing framework that strives to be simple, general, and flexible. We also provide a decoder for this pr...
Abstract. We propose a new unsupervised training method for acquiring probability models that accurately segment Chinese character sequences into words. By constructing a core lexi...
Mixed Group Ranks is a parametric method for combining rank based classiers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...
In many different application areas, e.g. space observation systems or engineering systems of world-wide operating companies, there is a need for an efficient distributed intersect...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...
Existing wavelet-based image denoising techniques all assume a probability model of wavelet coefficients that has zero mean, such as zero-mean Laplacian, Gaussian, or generalized ...