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» Learning to learn with the informative vector machine
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ALT
2006
Springer
16 years 3 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
MLG
2007
Springer
16 years 29 days ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
ACL
2006
15 years 8 months ago
Japanese Dependency Parsing Using Co-Occurrence Information and a Combination of Case Elements
In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of information not consi...
Takeshi Abekawa, Manabu Okumura
COLT
2001
Springer
15 years 11 months ago
Limitations of Learning via Embeddings in Euclidean Half-Spaces
The notion of embedding a class of dichotomies in a class of linear half spaces is central to the support vector machines paradigm. We examine the question of determining the mini...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
ECTEL
2007
Springer
16 years 1 months ago
MACE - Enriching Architectural Learning Objects for Experience Multiplication
Education in architecture requires access to a broad range of learning materials to develop flexibility and creativity in design. The learning material is compromised of textual an...
Moritz Stefaner, Elisa Dalla Vecchia, Massimiliano...