We propose a learning-based approach for full-body pose reconstruction from extremely sparse upper body tracking data, obtained virtual reality (VR) device. leverage conditional variational autoencoder with gated recurrent units to synthesize plausible and temporally coherent motions 4-point (head, hands, waist positions orientations). To avoid synthesizing implausible poses, we novel sample se...

We consider the problem of minimizing expected prediction cost, when there are costs associated with determining attribute values. Given a Boolean hypothesis function and a sample of this function, we seek to minimize the average prediction cost over the sample (Sample-BFE problem). We define and explore two different versions of this problem and show how existing work can be used to yield appr...

OBJECTIVES Recent guidelines recommend that all cirrhotic patients should undergo endoscopic screening for esophageal varices. That identifying cirrhotic patients with esophageal varices by noninvasive predictors would allow for the restriction of the performance of endoscopy to patients with a high risk of having varices. This study aimed to develop a decision model based on classification and...

A basic problem in empirical economics involves using data from one domain to make out-of-sample predictions for a different, but related environment. When the choice data are binary, a canonical method for making these types of predictions is the logistic choice model. We investigate if it is possible to improve out-of-sample predictions by changing two aspects of the canonical approach: 1) Us...

market crash is a phenomenon which occurs in stock markets occasionally and leads to loss of the investors’ wealth and assets in a relatively short period of time. therefore, attempts for prediction of this phenomenon are of much importance for the investors, financial institutions and government. to this date, numerous and varied studies have been carried out for predicting and modeling  stock...

MicroRNAs (miRNAs) are small molecular non-coding RNAs that have important roles in the post-transcriptional mechanism of animals and plants. They are commonly 21-25 nucleotides (nt) long and derived from 60-90 nt RNA hairpin structures, called miRNA hairpins. A larger number of sequence segments in the human genome have been computationally identified with such 60-90 nt hairpins, however the m...

In this thesis we present the novel semi-supervised network-based algorithm P-Net, which is able to rank and classify patients with respect to a specific phenotype or clinical outcome under study. The peculiar and innovative characteristic of this method is that it builds a network of samples/patients, where the nodes represent the samples and the edges are functional or genetic relationships b...

Dynamic risk prediction is a powerful tool to estimate the future risk of study subjects with data involves time-dependent information, including repeatedly measured covariates, intermediate events, and time-varying covariate effects. The quantity of interest for dynamic risk prediction is the probability of failure at the prediction horizon time conditional on the status at the prediction base...

Bayesian predictive functions for future observations from a generalized Pareto distribution based on generalized order statistics are obtained. Two cases are considered unknown one parameter and unknown two parameters. We also consider two cases fixed sample size and random sample size. The Bayesian predictive functions are specialized to ordinary order statistics, progressive type II censorin...

In recent years, the volume of traffic is rapidly increasing. When vehicles running through the tunnel are more intensive or move slowly, the tunnel environment occurs deteriorated sharply, which affects the normal operation of the vehicle in the tunnel. This paper uses the result of previous mining association rules to select feature items and to establish four training samples divided by time...