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ICML
2005
IEEE
14 years 11 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
TSP
2008
117views more  TSP 2008»
13 years 10 months ago
A Theory for Sampling Signals From a Union of Subspaces
One of the fundamental assumptions in traditional sampling theorems is that the signals to be sampled come from a single vector space (e.g. bandlimited functions). However, in many...
Yue M. Lu, Minh N. Do
ICML
2000
IEEE
14 years 11 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
MLG
2007
Springer
14 years 5 months 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
DAC
1994
ACM
14 years 3 months ago
Rectilinear Steiner Trees with Minimum Elmore Delay
We provide a new theoretical framework for constructing Steiner routing trees with minimum Elmore delay. Earlier work [3, 13] has established Elmore delay as a high delity estima...
Kenneth D. Boese, Andrew B. Kahng, Bernard A. McCo...