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» Geometry-aware metric learning
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NAACL
2007
15 years 4 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
IJCAI
2007
15 years 4 months ago
Improving Embeddings by Flexible Exploitation of Side Information
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
Ali Ghodsi, Dana F. Wilkinson, Finnegan Southey
ICASSP
2011
IEEE
14 years 6 months ago
Theoretical analyses on a class of nested RKHS's
One of central topics of kernel machines in the field of machine learning is a model selection, especially a selection of a kernel or its parameters. In our previous work, we dis...
Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaak...
CORR
2006
Springer
96views Education» more  CORR 2006»
15 years 3 months ago
Metric entropy in competitive on-line prediction
Competitive on-line prediction (also known as universal prediction of individual sequences) is a strand of learning theory avoiding making any stochastic assumptions about the way...
Vladimir Vovk
ECSQARU
2001
Springer
15 years 7 months ago
An Empirical Investigation of the K2 Metric
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Christian Borgelt, Rudolf Kruse