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NIPS
2008
15 years 7 months ago
Deep Learning with Kernel Regularization for Visual Recognition
In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Kai Yu, Wei Xu, Yihong Gong
184
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NIPS
2004
15 years 7 months ago
Semi-supervised Learning on Directed Graphs
Given a directed graph in which some of the nodes are labeled, we investigate the question of how to exploit the link structure of the graph to infer the labels of the remaining u...
Dengyong Zhou, Bernhard Schölkopf, Thomas Hof...
ICML
1999
IEEE
16 years 7 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
AAAI
2012
13 years 8 months ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
WWW
2004
ACM
16 years 7 months ago
Personalization in distributed e-learning environments
Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize p...
Peter Dolog, Nicola Henze, Wolfgang Nejdl, Michael...