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» Semisupervised learning from dissimilarity data
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ICML
2004
IEEE
15 years 10 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
AAAI
2011
13 years 9 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
71
Voted
AAAI
2007
14 years 12 months ago
Learning Large Scale Common Sense Models of Everyday Life
Recent work has shown promise in using large, publicly available, hand-contributed commonsense databases as joint models that can be used to infer human state from day-to-day sens...
William Pentney, Matthai Philipose, Jeff A. Bilmes...
68
Voted
ICMCS
2007
IEEE
112views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Detecting Unsafe Driving Patterns using Discriminative Learning
We propose a discriminative learning approach for fusing multichannel sequential data with application to detect unsafe driving patterns from multi-channel driving recording data....
Yue Zhou, Wei Xu, Huazhong Ning, Yihong Gong, Thom...
ECCV
2008
Springer
15 years 11 months ago
VideoCut: Removing Irrelevant Frames by Discovering the Object of Interest
We propose a novel method for removing irrelevant frames from a video given user-provided frame-level labeling for a very small number of frames. We first hypothesize a number of c...
David Liu, Gang Hua, Tsuhan Chen