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ICML
2008
IEEE
14 years 9 months ago
Detecting statistical interactions with additive groves of trees
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
Daria Sorokina, Rich Caruana, Mirek Riedewald, Dan...
ML
2002
ACM
178views Machine Learning» more  ML 2002»
13 years 7 months ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
VTS
2008
IEEE
70views Hardware» more  VTS 2008»
14 years 2 months ago
A Statistical Approach to Characterizing and Testing Functionalized Nanowires
Unlike the top-down photolithographic CMOS VLSI process, cost-effective bulk fabrication of nanodevices calls for a bottom-up approach, generally called self-assembly. Selfassembl...
James Dardig, Haralampos-G. D. Stratigopoulos, Eri...
ICML
2007
IEEE
14 years 9 months ago
Statistical predicate invention
We propose statistical predicate invention as a key problem for statistical relational learning. SPI is the problem of discovering new concepts, properties and relations in struct...
Stanley Kok, Pedro Domingos
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar