Tatiana Shpakova

2 accepted papers

2019

Hyper-parameter Learning for Sparse Structured Probabilistic Models

Tatiana Shpakova, Francis R. Bach, Mike E. Davies

ICASSP 2019accepted

In this paper, we consider the estimation of hyperparameters for regularization terms commonly used for obtaining structured sparse parameters in signal estimation problems, such as signal denoising. By considering the convex regularization terms as negative log-densities, we propose approximate max…

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2016

Parameter Learning for Log-supermodular Distributions

Tatiana Shpakova, Francis Bach

NeurIPS 2016poster

We consider log-supermodular models on binary variables, which are probabilistic models with negative log-densities which are submodular. These models provide probabilistic interpretations of common combinatorial optimization tasks such as image segmentation. In this paper, we focus primarily on par…

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