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ICML
2009
IEEE
16 years 4 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
CDC
2009
IEEE
137views Control Systems» more  CDC 2009»
15 years 8 months ago
Kernel regression for travel time estimation via convex optimization
—We develop an algorithm aimed at estimating travel time on segments of a road network using a convex optimization framework. Sampled travel time from probe vehicles are assumed ...
Sebastien Blandin, Laurent El Ghaoui, Alexandre M....
121
Voted
FOCS
2006
IEEE
15 years 9 months ago
Hardness of Learning Halfspaces with Noise
Learning an unknown halfspace (also called a perceptron) from labeled examples is one of the classic problems in machine learning. In the noise-free case, when a halfspace consist...
Venkatesan Guruswami, Prasad Raghavendra
115
Voted
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 9 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
114
Voted
FINTAL
2006
15 years 7 months ago
Regular Approximation of Link Grammar
We present a regular approximation of Link Grammar, a dependency-type formalism with context-free expressive power, as a first step toward a finite-state joint inference system. Th...
Filip Ginter, Sampo Pyysalo, Jorma Boberg, Tapio S...