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NIPS
2004
13 years 10 months ago
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation
Bayesian Regularization and Nonnegative Deconvolution (BRAND) is proposed for estimating time delays of acoustic signals in reverberant environments. Sparsity of the nonnegative f...
Yuanqing Lin, Daniel D. Lee
JMLR
2010
163views more  JMLR 2010»
13 years 3 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray

Publication
352views
14 years 4 months ago
Efficient methods for near-optimal sequential decision making under uncertainty
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
Christos Dimitrakakis
CORR
2010
Springer
93views Education» more  CORR 2010»
13 years 8 months ago
On MMSE and MAP Denoising Under Sparse Representation Modeling Over a Unitary Dictionary
Among the many ways to model signals, a recent approach that draws considerable attention is sparse representation modeling. In this model, the signal is assumed to be generated a...
Javier Turek, Irad Yavneh, Matan Protter, Michael ...
NIPS
2004
13 years 10 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu