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» Learning Object Representations Using Sequential Patterns
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CVPR
2005
IEEE
15 years 17 hour ago
Learning Appearance Manifolds from Video
The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this lowdimensional rep...
Ali Rahimi, Ben Recht, Trevor Darrell
SEMCO
2009
IEEE
14 years 4 months ago
Ontology Extraction from Existing Educational Content to Improve Personalized e-Learning Experiences
Nowadays, the use of domain ontologies in e-Learning applications is rapidly increasing due to the important role they play in knowledge representation, sharing of didactical mate...
Nicola Capuano, Luca Dell'Angelo, Francesco Orciuo...
CORR
2010
Springer
148views Education» more  CORR 2010»
13 years 5 months ago
A Unifying View of Multiple Kernel Learning
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
Marius Kloft, Ulrich Rückert, Peter L. Bartle...
CVPR
2007
IEEE
15 years 17 hour ago
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
A popular approach to problems in image classification is to represent the image as a bag of visual words and then employ a classifier to categorize the image. Unfortunately, a si...
Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukt...
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 10 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos