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COGSCI
2010
114views more  COGSCI 2010»
13 years 5 months ago
Direct Associations or Internal Transformations? Exploring the Mechanisms Underlying Sequential Learning Behavior
We evaluate two broad classes of cognitive mechanisms that might support the learning of sequential patterns. According to the first, learning is based on the gradual accumulation...
Todd M. Gureckis, Bradley C. Love
PPSN
2004
Springer
13 years 10 months ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
ML
2007
ACM
144views Machine Learning» more  ML 2007»
13 years 5 months ago
Invariant kernel functions for pattern analysis and machine learning
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
Bernard Haasdonk, Hans Burkhardt
ICCV
2011
IEEE
12 years 5 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
BIRTHDAY
2005
Springer
13 years 11 months ago
Towards Comprehensive Computational Models for Plan-Based Control of Autonomous Robots
In this paper we present an overview of recent developments in the plan-based control of autonomous robots. We identify computational principles that enable autonomous robots to a...
Michael Beetz