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ML
2006
ACM
110views Machine Learning» more  ML 2006»
15 years 1 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
ML
2006
ACM
131views Machine Learning» more  ML 2006»
15 years 1 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ICML
1995
IEEE
16 years 2 months ago
Residual Algorithms: Reinforcement Learning with Function Approximation
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
Leemon C. Baird III
ICML
2006
IEEE
15 years 7 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
TASLP
2008
229views more  TASLP 2008»
15 years 1 months ago
System Combination for Machine Translation of Spoken and Written Language
This paper describes an approach for computing a consensus translation from the outputs of multiple machine translation (MT) systems. The consensus translation is computed by weigh...
Evgeny Matusov, Gregor Leusch, Rafael E. Banchs, N...