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107
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ICML
2005
IEEE
16 years 4 months ago
Object correspondence as a machine learning problem
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
Bernhard Schölkopf, Florian Steinke, Volker B...
FLAIRS
2007
15 years 6 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
PPSN
2004
Springer
15 years 9 months ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
96
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SIGCSE
2000
ACM
91views Education» more  SIGCSE 2000»
15 years 8 months ago
Machine learning in the liberal arts curriculum
Machine learning is typically considered a graduate-level course with an artificial intelligence course as a prerequisite. However, it does not need to be positioned this way, and...
Clare Bates Congdon
MICAI
2010
Springer
15 years 2 months ago
Recognizing Textual Entailment Using a Machine Learning Approach
We present our experiments on Recognizing Textual Entailment based on modeling the entailment relation as a classification problem. As features used to classify the entailment pair...
Miguel Angel Ríos Gaona, Alexander F. Gelbu...