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GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
13 years 11 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
FLOPS
2006
Springer
13 years 11 months ago
Convergence in Language Design: A Case of Lightning Striking Four Times in the Same Place
What will a definitive programming language look like? By definitive language I mean a programming language that gives good soat its level of abstraction, allowing computer science...
Peter Van Roy
ICML
2008
IEEE
14 years 8 months ago
Efficiently solving convex relaxations for MAP estimation
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
M. Pawan Kumar, Philip H. S. Torr
ICML
2003
IEEE
14 years 8 months ago
Planning in the Presence of Cost Functions Controlled by an Adversary
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
JMLR
2012
11 years 10 months ago
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...