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» Learning Algorithms for Domain Adaptation
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IJCNN
2006
IEEE
15 years 9 months ago
A Comparison between Recursive Neural Networks and Graph Neural Networks
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
CVPR
2010
IEEE
15 years 10 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
123
Voted
ML
2008
ACM
15 years 2 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
ICONIP
2007
15 years 4 months ago
Natural Conjugate Gradient in Variational Inference
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
AIA
2006
15 years 4 months ago
Some Experiments Around a Neural Network for Multimodal Associations
This paper presents a study of the model of triple BAM by [11] which is an improved variation of the original BAM model by [7]. This class of model aims at integrating different s...
Yann Boniface, Reghis Abdelmalek