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ICML
2009
IEEE
16 years 7 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
ICML
2009
IEEE
16 years 7 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos
KDD
2005
ACM
158views Data Mining» more  KDD 2005»
16 years 6 months ago
Adversarial learning
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
Daniel Lowd, Christopher Meek
CVPR
2010
IEEE
16 years 2 months ago
Boundary Learning by Optimization with Topological Constraints
Recent studies have shown that machine learning can improve the accuracy of detecting object boundaries in images. In the standard approach, a boundary detector is trained by mini...
Viren Jain, Benjamin Bollmann, Bobby Kasthuri, Ken...
TEI
2009
ACM
112views Hardware» more  TEI 2009»
16 years 28 days ago
The effect of representation location on interaction in a tangible learning environment
Drawing on the ‘representation’ TUI framework [21], this paper reports a study that investigated the concept of ‘representation location’ and its effect on interaction and...
Sara Price, Taciana Pontual Falcão, Jennife...