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» Learning with Neural Networks in the Domain of Graphs
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FLAIRS
2007
14 years 12 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
ECCV
2008
Springer
15 years 11 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
IPPS
1998
IEEE
15 years 1 months ago
Multiprocessor Scheduling Using Mean-Field Annealing
This paper presents our work on the static task scheduling model using the mean-field annealing (MFA) technique. Mean-field annealing is a technique of thermostatic annealing that...
Shaharuddin Salleh, Albert Y. Zomaya
102
Voted
ICRA
2009
IEEE
151views Robotics» more  ICRA 2009»
14 years 7 months ago
Surface identification using simple contact dynamics for mobile robots
This paper describes an approach to surface identification in the context of mobile robotics, applicable to supervised and unsupervised learning. The identification is based on ana...
Philippe Giguère, Gregory Dudek
JMLR
2010
143views more  JMLR 2010»
14 years 4 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov