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ICML
2009
IEEE
16 years 2 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
INFOCOM
1999
IEEE
15 years 5 months ago
Inference of Multicast Routing Trees and Bottleneck Bandwidths Using End-to-end Measurements
Abstract-- The efficacy of end-to-end multicast transport protocols depends critically upon their ability to scale efficiently to a large number of receivers. Several research mult...
Sylvia Ratnasamy, Steven McCanne
JMLR
2010
134views more  JMLR 2010»
14 years 8 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
KES
2000
Springer
15 years 5 months ago
Hierarchical growing cell structures: TreeGCS
We propose a hierarchical, unsupervised clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS) neural network of Fritzke. Our algorithm improves an inconsisten...
Victoria J. Hodge, James Austin
CORR
2011
Springer
261views Education» more  CORR 2011»
14 years 8 months ago
Convex and Network Flow Optimization for Structured Sparsity
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...