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» Learning Distance Functions using Equivalence Relations
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ECAI
2008
Springer
14 years 11 months ago
Reinforcement Learning with the Use of Costly Features
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
Robby Goetschalckx, Scott Sanner, Kurt Driessens
97
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ICPR
2010
IEEE
15 years 3 months ago
A Meta-Learning Approach to Conditional Random Fields Using Error-Correcting Output Codes
—We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a...
Francesco Ciompi, Oriol Pujol, Petia Radeva
ICASSP
2011
IEEE
14 years 1 months ago
Fourier expansion of hammerstein models for nonlinear acoustic system identification
We consider the task of acoustic system identification, where the input signal undergoes a memoryless nonlinear transformation before convolving with an unknown linear system. We...
Sarmad Malik, Gerald Enzner
GIS
2009
ACM
15 years 1 months ago
Dynamic network data exploration through semi-supervised functional embedding
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
Alexei Pozdnoukhov
ECAI
2004
Springer
15 years 1 months ago
Avoiding Data Overfitting in Scientific Discovery: Experiments in Functional Genomics
Functional genomics is a typical scientific discovery domain characterized by a very large number of attributes (genes) relative to the number of examples (observations). The dang...
Dragan Gamberger, Nada Lavrac