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TCS
2011
15 years 2 months ago
Smart PAC-learners
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
Malte Darnstädt, Hans-Ulrich Simon
235
Voted
AAAI
2012
13 years 9 months ago
Sparse Probabilistic Relational Projection
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Wu-Jun Li, Dit-Yan Yeung
JCB
2006
185views more  JCB 2006»
15 years 7 months ago
A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
295
Voted
CVPR
2012
IEEE
13 years 9 months ago
Boosting bottom-up and top-down visual features for saliency estimation
Despite significant recent progress, the best available visual saliency models still lag behind human performance in predicting eye fixations in free-viewing of natural scenes. ...
Ali Borji
215
Voted
CVPR
2003
IEEE
16 years 9 months ago
Representation and Detection of Deformable Shapes
We describe some techniques that can be used to represent and detect deformable shapes in images. The main difficulty with deformable template models is the very large or infinite...
Pedro F. Felzenszwalb
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