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ACL
1998
13 years 11 months ago
Maximum Entropy Model Learning of the Translation Rules
This paper proposes a learning method of translation rules from parallel corpora. This method applies the maximum entropy principle to a probabilistic model of translation rules. ...
Kengo Sato, Masakazu Nakanishi
COCO
2001
Springer
149views Algorithms» more  COCO 2001»
14 years 2 months ago
Quantum versus Classical Learnability
Motivated by recent work on quantum black-box query complexity, we consider quantum versions of two wellstudied models of learning Boolean functions: Angluin’s model of exact le...
Rocco A. Servedio, Steven J. Gortler
ICML
2004
IEEE
14 years 11 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
NIPS
2004
13 years 11 months ago
Non-Local Manifold Tangent Learning
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
Yoshua Bengio, Martin Monperrus
ICML
2008
IEEE
14 years 11 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin