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We describe a mixture density propagation algorithm to estimate 3D human motion in monocular video sequences based on observations encoding the appearance of image silhouettes. Our approach is discriminative rather than generative, therefore it does not require the probabilistic inversion of a predictive observation model. Instead, it uses a large human(More)
Reliable 3D tracking is still a difficult task. Most parametrized 3D deformable models rely on the accurate extraction of image features for updating their parameters, and are prone to failures when the underlying feature distribution assumptions are invalid. Active Shape Models (ASMs), on the other hand, are based on learning, and thus require fewer(More)
This paper presents our joint research efforts on big data benchmarking with several industrial partners. Considering the complexity, diversity, workload churns, and rapid evolution of big data systems, we take an incre-mental approach in big data benchmarking. For the first step, we pay attention to search engines, which are the most important domain in(More)
A large volume of honey bee (Apis mellifera) tag-seq was obtained to identify differential gene expression via Solexa/lllumina Digital Gene Expression tag profiling (DGE) based on next generation sequencing. In total, 4,286,250 (foragers) and 3,422,327 (nurses) clean tags were sequenced, 24,568 (foragers) and 13,134 (nurses) distinct clean tags could not be(More)
Small interfering RNAs (siRNAs) silence the expression of specific target genes by mediating RNA interference (RNAi) in mammalian cells. siRNAs have not only been widely used as a valuable tool for functional genomics research, but they also have demonstrated great potential in biomedical therapeutic applications for diseases caused by abnormal gene(More)
We describe a mixture density propagation algorithm to estimate 3D human motion in monocular video sequences, based on observations encoding the appearance of image silhouettes. Our approach is discrimi-native rather than generative, therefore it does not require the probabilistic inversion of a predictive observation model. Instead, it uses a large human(More)
We present a conditional temporal probabilistic framework for reconstructing 3D human motion in monocular video based on descriptors encoding image silhouette observations. For computational efficiency we restrict visual inference to low-dimensional kernel induced non-linear state spaces. Our methodology (kBME) combines kernel PCA-based non-linear(More)
For many clinical studies in cancer, germline DNA is prospectively collected for the purpose of discovering or validating single-nucleotide polymorphisms (SNPs) associated with clinical outcomes. The primary clinical endpoint for many of these studies are time-to-event outcomes such as time of death or disease progression which are subject to censoring(More)
Insulin receptor substrate (IRS) proteins play important roles by acting as a platform in transducing signals from transmembrane receptors upon growth factor stimulation. Although tyrosine phosphorylation on IRS proteins plays critical roles in signal transduction, phosphorylation of IRS proteins on serine/threonine residues is believed to play various(More)
Two-stage randomized trials are growing in importance in developing adaptive treatment strategies, i.e. treatment policies or dynamic treatment regimes. Usually, the first stage involves randomization to one of the several initial treatments. The second stage of treatment begins when an early nonresponse criterion or response criterion is met. In the(More)