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ICML
2000
IEEE
14 years 2 months ago
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning
Cognitive modeling with neural networks unrealistically ignores the role of knowledge in learning by starting from random weights. It is likely that effective use of knowledge by ...
Thomas R. Shultz, François Rivest
ICML
2003
IEEE
14 years 10 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
ICML
2005
IEEE
14 years 10 months ago
Learning predictive representations from a history
Predictive State Representations (PSRs) have shown a great deal of promise as an alternative to Markov models. However, learning a PSR from a single stream of data generated from ...
Eric Wiewiora
COLING
2010
13 years 4 months ago
Learning Phrase Boundaries for Hierarchical Phrase-based Translation
Hierarchical phrase-based models provide a powerful mechanism to capture non-local phrase reorderings for statistical machine translation (SMT). However, many phrase reorderings a...
Zhongjun He, Yao Meng, Hao Yu
ECML
2006
Springer
14 years 1 months ago
Bayesian Learning of Markov Network Structure
Abstract. We propose a simple and efficient approach to building undirected probabilistic classification models (Markov networks) that extend na
Aleks Jakulin, Irina Rish