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Automatic Recognition of Facial Actions in Spontaneous Expressions

by Marian Stewart Bartlett, Gwen C. Littlewort, Mark G. Frank, Claudia Lainscsek, Ian R. Fasel, Javier R. Movellan
"... Abstract — Spontaneous facial expressions differ from posed expressions in both which muscles are moved, and in the dynamics of the movement. Advances in the field of automatic facial expression measurement will require development and assessment on spontaneous behavior. Here we present preliminary ..."
Abstract - Cited by 147 (23 self) - Add to MetaCart
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

Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features

by Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Michael Scheuering, Dorin Comaniciu - IEEE TRANSACTIONS ON MEDICAL IMAGING , 2008
"... We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a non-trivial task since the ..."
Abstract - Cited by 102 (43 self) - Add to MetaCart
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

Learning Subjective Functions with Large Margins

by Claude-nicolas Fiechter, Seth Rogers - Stanford University , 2000
"... 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 pr ..."
Abstract - Cited by 27 (1 self) - Add to MetaCart
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

Whom You Know Matters: Venture Capital Networks and Investment Performance,

by Yael Hochberg , Alexander Ljungqvist , Yang Lu , Steve Drucker , Jan Eberly , Eric Green , Yaniv Grinstein , Josh Lerner , Laura Lindsey , Max Maksimovic , Roni Michaely , Maureen O'hara , Ludo Phalippou Mitch Petersen , Jesper Sorensen , Per Strömberg Morten Sorensen , Yael Hochberg , Johnson - Journal of Finance , 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm's-length, spot-market transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
Abstract - Cited by 138 (8 self) - Add to MetaCart
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

Who will follow you back? reciprocal relationship prediction

by John Hopcroft, Tiancheng Lou, Jie Tang - In CIKM’11 , 2011
"... 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 the forma ..."
Abstract - Cited by 46 (14 self) - Add to MetaCart
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

Optimizing mean reciprocal rank for person re-identification

by Yang Wu, Masayuki Mukunoki, Takuya Funatomi, Michihiko Minoh, Shihong Lao - In AVSS , 2011
"... Person re-identification is one of the most challenging is-sues in network-based surveillance. The difficulties mainly come from the great appearance variations induced by il-lumination, camera view and body pose changes. Maybe influenced by the research on face recognition and gen-eral object recog ..."
Abstract - Cited by 11 (6 self) - Add to MetaCart
-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

Learning a Maximum Margin Subspace for Image Retrieval

by Xiaofei He, Deng Cai, Jiawei Han , 2008
"... One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap, relevance feedback is introduced into image retrieval. With the user-provided information, a classifier can be learne ..."
Abstract - Cited by 25 (5 self) - Add to MetaCart
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

Marginalized Stacked Denoising Autoencoders

by Minmin Chen, Zhixiang (eddie Xu, Kilian Q. Weinberger, Fei Sha
"... 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 learning ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
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

39 Learning to Predict Reciprocity and Triadic Closure in Social Networks

by Tiancheng Lou, John Hopcroft
"... 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 of the fund ..."
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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

5 Learning to Predict Reciprocity and Triadic Closure in Social Networks

by Tiancheng Lou, Jie Tang, John Hopcroft , 2013
"... 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 of the fund ..."
Abstract - Add to MetaCart
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
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