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NAACL
2003
13 years 10 months ago
Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
We address the text-to-text generation problem of sentence-level paraphrasing — a phenomenon distinct from and more difficult than word- or phrase-level paraphrasing. Our appro...
Regina Barzilay, Lillian Lee
IDA
2002
Springer
13 years 8 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
PCI
2005
Springer
14 years 2 months ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
EMNLP
2007
13 years 10 months ago
LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
Rahul Bhagat, Patrick Pantel, Eduard H. Hovy
NIPS
2004
13 years 10 months ago
Sampling Methods for Unsupervised Learning
We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algo...
Robert Fergus, Andrew Zisserman, Pietro Perona