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NAACL
2010
13 years 5 months ago
From Baby Steps to Leapfrog: How "Less is More" in Unsupervised Dependency Parsing
We present three approaches for unsupervised grammar induction that are sensitive to data complexity and apply them to Klein and Manning's Dependency Model with Valence. The ...
Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jura...
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
12 years 11 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
AAAI
2012
11 years 10 months ago
Ontological Smoothing for Relation Extraction with Minimal Supervision
Relation extraction, the process of converting natural language text into structured knowledge, is increasingly important. Most successful techniques use supervised machine learni...
Congle Zhang, Raphael Hoffmann, Daniel S. Weld
SIGUCCS
2003
ACM
14 years 26 days ago
Macintosh OS X: a smooth migration
The Ringling School of Art and Design is a fully accredited four year college of visual art and design with a student population of approximately 1000. The Ringling School has ach...
Scott E. Hanselman, Mahmoud Pegah
COLT
1999
Springer
13 years 12 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon