In the past, many children born with complex congenital heart defects (CHDs) underwent palliative procedures to avoid the use of cardiopulmonary bypass, which typically is required for prolonged corrective procedures. The risk of mortality was prohibitive, especially in newborns; therefore, efforts were directed toward palliative procedures until the children grew big enough for a definitive re...

Pulmonary function testing is a vital part of the assessment process for thoracic surgery. However, for other types of surgery there is no evidence that spirometry is more effective than history and examination in predicting postoperative pulmonary complications in patients with known chronic lung conditions. Furthermore specific spirometric values (e.g. the FEV1) cannot be taken as prohibitive...

Dimensionality reduction is one of the important preprocessing steps in practical pattern recognition. SEmi-supervised Local Fisher discriminant analysis (SELF)— which is a semi-supervised and local extension of Fisher discriminant analysis—was shown to work excellently in experiments. However, when data dimensionality is very high, a naive use of SELF is prohibitive due to high computational c...

Virtual colonoscopy on powerful workstations has the distinct advantage of interactive navigation, as opposed to passive viewing of cine loops or pre-computed movies. Because of the prohibitive cost of hardware, only passive displays have been feasible for the wide-scale deployment required for mass screening. The purpose of our work is to compare low-cost commodity hardware as an effective too...

Named Entity (NE) information is critical for Information Extraction (IE) tasks. However, the cost of manually annotating sufficient data for training purposes, especially for multiple languages, is prohibitive, meaning automated methods for developing resources are crucial. We investigate the automatic generation of NE annotated data in German from Wikipedia. By incorporating structural featur...

Aims High resolution computed tomography (CT) image based finite element (FE) models have been widely applied to assess the mechanical properties of human trabecular bone. However, the prohibitive computational cost of voxel-based FE models limits its clinical applications, especially in whole bone strength prediction by nonlinear FE analysis. There is a strong need for an alternative modeling ...

The computation and memory required for kernel machines with N training samples is at least O(N). Such a complexity is significant even for moderate size problems and is prohibitive for large datasets. We present an approximation technique based on the improved fast Gauss transform to reduce the computation to O(N). We also give an error bound for the approximation, and provide experimental res...

We consider the problem of learning from distributed data in the agnostic setting, i.e., in the presence of arbitrary forms of noise. Our main contribution is a general distributed boosting-based procedure for learning an arbitrary concept space, that is simultaneously noise tolerant, communication efficient, and computationally efficient. This improves significantly over prior works that were ...

The curse of dimensionality gives rise to prohibitive computational requirements that render infeasible the exact solution of largescale stochastic control problems. We study an efficient method based on linear programming for approximating solutions to such problems. The approach "fits" a linear combination of preselected basis functions to the dynamic programming costtogo function. We develop...

Robot learning in simulation is a promising alternative to the prohibitive sample cost of learning in the physical world. Unfortunately, policies learned in simulation often perform worse than hand-coded policies when applied on the physical robot. This paper proposes a new algorithm for learning in simulation – Grounded Action Transformation – and applies it to learning of humanoid bipedal loc...