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144
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CVPR
2006
IEEE
16 years 4 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
130
Voted
NIPS
1998
15 years 3 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
144
Voted
ICMLA
2010
15 years 15 days ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
139
Voted
ECCV
2010
Springer
15 years 3 months ago
Activities as Time Series of Human Postures
Abstract. This paper presents an exemplar-based approach to detecting and localizing human actions, such as running, cycling, and swinging, in realistic videos with dynamic backgro...
William Brendel, Sinisa Todorovic
125
Voted
CVPR
2012
IEEE
13 years 5 months ago
Bilevel sparse coding for coupled feature spaces
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...
Jianchao Yang, Zhaowen Wang, Zhe Lin, Xianbiao Shu...