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» Learning to generalize for complex selection tasks
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GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
13 years 10 months ago
Evolution of Goal-Directed Behavior from Limited Information in a Complex Environment
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...
Matthew R. Glickman, Katia P. Sycara
SLSFS
2005
Springer
13 years 12 months ago
Generalization Bounds for Subspace Selection and Hyperbolic PCA
We present a method which uses example pairs of equal or unequal class labels to select a subspace with near optimal metric properties in a kernel-induced Hilbert space. A represen...
Andreas Maurer
NIPS
2007
13 years 7 months ago
A general agnostic active learning algorithm
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni
ALIFE
2010
13 years 5 months ago
The Utility of Evolving Simulated Robot Morphology Increases with Task Complexity for Object Manipulation
Embodied artificial intelligence argues that the body and brain play equally important roles in the generation of adaptive behavior. An increasingly common approach therefore is to...
Josh Bongard
JMLR
2006
137views more  JMLR 2006»
13 years 6 months ago
Bounds for Linear Multi-Task Learning
Abstract. We give dimension-free and data-dependent bounds for linear multi-task learning where a common linear operator is chosen to preprocess data for a vector of task speci...c...
Andreas Maurer