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» Semi-Supervised Random Forests
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CVPR
2007
IEEE
16 years 1 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs
ECCV
2008
Springer
16 years 1 months ago
Segmentation and Recognition Using Structure from Motion Point Clouds
We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3...
Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 2 days ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
CIDM
2009
IEEE
15 years 6 months ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
ICSM
2008
IEEE
15 years 6 months ago
Understanding the rationale for updating a function's comment
Up-to-date comments are critical for the successful evolution of a software application. When modifying a function, developers may update the comment associated with the function ...
Haroon Malik, Istehad Chowdhury, Hsiao-Ming Tsou, ...