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JMLR
2008
230views more  JMLR 2008»
13 years 10 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
COLT
2005
Springer
14 years 4 months ago
Variations on U-Shaped Learning
The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements t...
Lorenzo Carlucci, Sanjay Jain, Efim B. Kinber, Fra...
AAAI
2004
14 years 7 days ago
Interactive Information Extraction with Constrained Conditional Random Fields
Information Extraction methods can be used to automatically "fill-in" database forms from unstructured data such as Web documents or email. State-of-the-art methods have...
Trausti T. Kristjansson, Aron Culotta, Paul A. Vio...
COLING
1996
14 years 5 days ago
Computational Complexity of Probabilistic Disambiguation by means of Tree-Grammars
This paper studies the computational complexity of disambiguation under probabilistic tree-grammars as in (Bod, 1992; Schabes and Waters, 1993). It presents a proof that the follo...
Khalil Sima'an