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» Learning Compressible Models
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ICASSP
2011
IEEE
14 years 1 months ago
Robust nonparametric regression by controlling sparsity
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
Gonzalo Mateos, Georgios B. Giannakis
SIGIR
2008
ACM
14 years 9 months ago
Compressed collections for simulated crawling
Collections are a fundamental tool for reproducible evaluation of information retrieval techniques. We describe a new method for distributing the document lengths and term counts ...
Alessio Orlandi, Sebastiano Vigna
TSP
2010
14 years 4 months ago
Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...
EUROGP
2000
Springer
15 years 1 months ago
Seeding Genetic Programming Populations
We show genetic programming (GP) populations can evolve under the influence of a Pareto multi-objective fitness and program size selection scheme, from "perfect" programs...
William B. Langdon, Peter Nordin
JMLR
2010
100views more  JMLR 2010»
14 years 4 months ago
Parametric Herding
A parametric version of herding is formulated. The nonlinear mapping between consecutive time slices is learned by a form of self-supervised training. The resulting dynamical syst...
Yutian Chen, Max Welling