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Discriminative training approaches like structural SVMs have shown much promise for building highly complex and accurate models in areas like natural language processing, protein structure prediction, and information retrieval. However, current training algorithms are computationally expensive or intractable on large datasets. To overcome this bottleneck,(More)
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. This results in two benefits. First, the added flexibility makes it possible to find sparser solutions of good quality, substantially speeding-up prediction. Second, the improved(More)
Machine Learning today offers a broad repertoire of methods for classification and regression. But what if we need to predict complex objects like trees, orderings, or alignments? Such problems arise naturally in natural language processing, search engines, and bioinformatics. The following explores a generalization of Support Vector Machines (SVMs) for(More)
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer vision. Focusing on large-margin methods, the most general (in terms of loss function and model structure) training algorithms known to date are based on cutting-plane approaches.(More)
Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features such as secondary structure, solvent accessibility, or evolutionary information improve sequence to structure alignment accuracy, but conventional generative estimation techniques for alignment models impose independence assumptions(More)
Thin solid films of hydroxypropylcellulose (HPC) have been investigated using synchrotron X-ray reflectivity. Evidence of preferential alignment of HPC molecules at the substrate surface is obtained. In the surface region the liquid crystalline domains ofHPC are preferentially oriented parallel to the substrate, whereas in the bulk they are mostly(More)
We have used synchrotron x rays to study three different liquids near solid-liquid interfaces. For either ultrathin (45-90 A) or thick ( approximately 5000 A) liquid films on silicon substrates, we find (on the basis of diffraction peaks or specular reflectivity data) that the molecules form 3-6 layers at the interface, with plane spacings close to the(More)
Protein threading is the problem of inferring the structure of a protein from its sequence by matching the sequence against a set of known structures. Unlike conventional sequence to sequence alignment tasks, alignment models for threading can exploit a rich set of features derived from the geometry of the known structure. To make use of these complex and(More)
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