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» Learning Rule Representations from Boolean Data
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94
Voted
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
14 years 10 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
107
Voted
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
15 years 7 months ago
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Debprakash Patnaik, Srivatsan Laxman, Naren Ramakr...
127
Voted
KDD
2009
ACM
249views Data Mining» more  KDD 2009»
16 years 1 months ago
Drosophila gene expression pattern annotation using sparse features and term-term interactions
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...

Publication
383views
16 years 23 days ago
Hunting Nessie -- Real-Time Abnormality Detection from Webcams
We present a data-driven, unsupervised method for unusual scene detection from static webcams. Such time-lapse data is usually captured with very low or varying framerate. This ...
Michael D. Breitenstein, Helmut Grabner, Luc Van G...
101
Voted
EACL
1989
ACL Anthology
15 years 1 months ago
It Would Be Much Easier If WENT Were GOED
The paper proposes a paradigmatic approach to morphological knowledge acquisition. It addresses the problem of learning from examples rules for word-forms analysis and synthesis. ...
Dan Tufis