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» Learning from Highly Structured Data by Decomposition
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UAI
2003
14 years 11 months ago
Robust Independence Testing for Constraint-Based Learning of Causal Structure
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
Denver Dash, Marek J. Druzdzel
EMNLP
2011
13 years 9 months ago
Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation
Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resourc...
Juri Ganitkevitch, Chris Callison-Burch, Courtney ...
IWPC
2000
IEEE
15 years 2 months ago
A Pattern Matching Framework for Software Architecture Recovery and Restructuring
This paper presents a framework for software architecture recovery and restructuring. The user specifies a high level abstraction view of the system using a structured pattern la...
Kamran Sartipi, Kostas Kontogiannis, Farhad Mavadd...
ICML
2007
IEEE
15 years 10 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
IDA
2009
Springer
15 years 4 months ago
Learning Natural Image Structure with a Horizontal Product Model
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
Urs Köster, Jussi T. Lindgren, Michael Gutman...