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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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NAACL
2007
13 years 8 months ago
Source-Language Features and Maximum Correlation Training for Machine Translation Evaluation
We propose three new features for MT evaluation: source-sentence constrained n-gram precision, source-sentence reordering metrics, and discriminative unigram precision, as well as...
Ding Liu, Daniel Gildea
ICMLC
2005
Springer
14 years 26 days ago
Kernel-Based Metric Adaptation with Pairwise Constraints
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
Hong Chang, Dit-Yan Yeung
BMCBI
2011
12 years 11 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
COLING
2010
13 years 1 months ago
Maximum Metric Score Training for Coreference Resolution
A large body of prior research on coreference resolution recasts the problem as a two-class classification problem. However, standard supervised machine learning algorithms that m...
Shanheng Zhao, Hwee Tou Ng
ECML
2006
Springer
13 years 11 months ago
EM Algorithm for Symmetric Causal Independence Models
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
Rasa Jurgelenaite, Tom Heskes