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An analysis of block sampling strategies in compressed sensing
Compressed Sensing blocks of measurements sampling continuous trajectories exact recovery,ℓ 1 minimization.
2013/6/17
Compressed sensing (CS) is a theory which guarantees the exact recovery of sparse signals from a few number of linear projections. The sampling schemes suggested by current CS theories are often of li...
Grouping Strategies and Thresholding for High Dimensional Linear Models
Structured sparsity Grouping, Learning Theory Non Linear Methods Block-thresholding coherence Wavelets
2012/9/19
The estimation problem in a high regression model with structured sparsity is investigated.An algorithm using a two steps block thresholding procedure called GR-LOL is provided.Convergence rates are p...
This paper presents Natural Evolution Strategies (NES), a recent family of algorithms that constitute a more principled approach to black-box optimization than established evolutionary algorithms.
Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies
Bayesian variable selection generalized linear models Gaussian processes
2011/7/5
This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data.
Identifying the consequences of dynamic treatment strategies: A decision-theoretic overview
Observational study Potential response Sequential decision theory
2010/10/19
We consider the problem of learning about and comparing the consequences of dynamic treatment strategies on the basis of observational data. We formulate this within a probabilistic decision-theoreti...
Strategies for prediction under imperfect monitoring
repeated games regret Hannan consistency imperfect monitoring
2010/4/26
We propose simple randomized strategies for sequential decision (or prediction) under imperfect monitoring, that is, when the decision maker (forecaster) does not have access to the past outcomes but ...