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MLG
2007
Springer
16 years 19 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
TCS
2008
15 years 6 months ago
Kernel methods for learning languages
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
SIAMCOMP
1998
86views more  SIAMCOMP 1998»
15 years 6 months ago
Exact Learning of Discretized Geometric Concepts
We first present an algorithm that uses membership and equivalence queries to exactly identify a discretized geometric concept defined by the union of m axis-parallel boxes in d-...
Nader H. Bshouty, Paul W. Goldberg, Sally A. Goldm...
IJCNN
2007
IEEE
16 years 24 days ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
DAGM
2004
Springer
15 years 12 months ago
Learning Depth from Stereo
We compare two approaches to the problem of estimating the depth of a point in space from observing its image position in two
Fabian H. Sinz, Joaquin Quiñonero Candela, ...