results on a task of facial action detection in spontaneous facial expressions. We employ a user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS). The system automatically detects frontal faces in the video stream and coded each

chambers. After determining the pose of the heart chambers, we estimate the 3D shape through learning-based boundary delineation. The proposed method has been extensively tested on the largest dataset (with 323 volumes from 137 patients) ever reported in the literature. To the best of our knowledge, our

In many optimization and decision problems the objective function can be expressed as a linear combination of competing criteria, the weights of which specify the relative importance of the criteria for the user. We consider the problem of learning such a "subjective" function from

to a subsequent funding round or exits successfully. This effect is large economically. For instance, the survival probability in the first funding round increases from the unconditional expectation of 66.8% to 72.4% for a onestandard-deviation increase in the lead VC's network centrality. Perhaps

We study the extent to which the formation of a two-way relation-ship can be predicted in a dynamic social network. A two-way (called reciprocal) relationship, usually developed from a one-way (parasocial) relationship, represents a more trustful relationship be-tween people. Understanding

-identification problem as a ranking problem and directly optimizes a listwise ranking function named Mean Reciprocal Rank (MRR), which is considered by us to be able to generate results closest to human expec-tations. Using a maximum-margin based structured learn-ing model, we are able to show improved re

be learned to distinguish between positive and negative examples. However, in real-world applications, the number of user feedbacks is usually too small compared to the dimensionality of the image space. In order to cope with the high dimensionality, we propose a novel semisupervised method

Stacked Denoising Autoencoders (SDAs) [4] have been used successfully in many learning scenarios and application domains. In short, denoising autoencoders (DAs) train one-layer neural networks to reconstruct input data from partial random corruption. The denoisers are then stacked into deep

We study how links are formed in social networks. In particular, we focus on investigating how a reciprocal (two-way) link, the basic relationship in social networks, is developed from a parasocial (one-way) relationship and how the relationships further develop into triadic closure, one

We study how links are formed in social networks. In particular, we focus on investigating how a reciprocal (two-way) link, the basic relationship in social networks, is developed from a parasocial (one-way) relationship and how the relationships further develop into triadic closure, one