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Št. zadetkov: 6
Active and Semi-Supervised Data Domain Description
Ulf Brefeld
Video in druga učna gradiva
Oznake: computer science;machine learning;semi-supervised learning
Data domain description techniques aim at deriving concise descriptions of objects belonging to a category of interest. For instance, the support vector domain description (SVDD) learns a hypersphere enclosing the bulk of provided unlabeled data such that points lying outside of the ball are conside ...
Leto: 2009 Vir: videolectures.net
Feature Selection for Density Level-Sets
Ulf Brefeld
Video in druga učna gradiva
Oznake:
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an efficient feature selection method for density level-set estimation where optimal kernel mixing coefficients and model para ...
Leto: 2009 Vir: videolectures.net
Semi-supervised Structured Prediction Models
Ulf Brefeld
Video in druga učna gradiva
Oznake: computer science;machine learning;structured output;semi-supervised learning
Leto: 2007 Vir: videolectures.net
Semi-supervised learning for SOP
Ulf Brefeld
Video in druga učna gradiva
Oznake:
Leto: 2016 Vir: videolectures.net
Exact and Approximate Inference for Annotating Graphs with Structural SVMs
Ulf Brefeld , Thoralf Klein , Tobias Scheffer
Video in druga učna gradiva
Oznake:
Training processes of structured prediction models such as structural SVMs involve frequent computations of the maximum-a-posteriori (MAP) prediction given a parameterized model. For specific output structures such as sequences or trees, MAP estimates can be computed efficiently by dynamic programmi ...
Leto: 2008 Vir: videolectures.net
Learning from Partially Annotated Sequences
Data & Web Mining Lab , Ulf Brefeld
Video in druga učna gradiva
Oznake: computer science;machine learning;semi-supervised learning
We study sequential prediction models in cases where only fragments of the sequences are annotated with the ground-truth. The task does not match the standard semi-supervised setting and is highly relevant in areas such as natural language processing, where completely labeled instances are expensive ...
Leto: 2011 Vir: videolectures.net
Št. zadetkov: 6
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