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JMLR
2008
230views more  JMLR 2008»
13 years 4 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
13 years 10 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
13 years 6 months 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
13 years 6 months 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