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NIPS
1997
15 years 8 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
ICMLA
2009
15 years 4 months ago
Learning Geographic Regions using Location Based Services in Next Generation Networks
Abstract--In this paper we apply classification to learn geographic regions using Location Based Services (LBS) in Next Generation Networks (NGN). We assume that the information in...
Yuheng He, Attila Bilgic
228
Voted
PR
2011
14 years 9 months ago
A novel multi-view learning developed from single-view patterns
The existing Multi-View Learning (MVL) learns how to process patterns with multiple information sources. In generalization this MVL is proven to have a significant advantage over...
Zhe Wang, Songcan Chen, Daqi Gao
193
Voted
TCS
2008
15 years 6 months ago
Kernel methods for learning languages
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
KDD
2009
ACM
132views Data Mining» more  KDD 2009»
16 years 7 months ago
Learning patterns in the dynamics of biological networks
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Chang Hun You, Lawrence B. Holder, Diane J. Cook