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<!DOCTYPE html>
<meta charset="UTF-8">
<html lang="en">
<head>
<title>Igor's Site</title>
<link href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css" rel="stylesheet">
<link href="style.css" rel="stylesheet">
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap-theme.min.css">
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<style type="text/css">
.bs-example{
margin: 20px;
}
</style>
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src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-MML-AM_CHTML">
</script>
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<body>
<nav class="navbar navbar-default">
<div class="container-fluid">
<!-- start un-collapsed navbar-->
<ul class="nav navbar-nav">
<li role=""><a href="index.html">Home</a></li>
<li class="dropdown active">
<a href="#" data-toggle="dropdown" class="dropdown-toggle" class="active">Research <b class="caret"></b></a>
<ul class="dropdown-menu">
<li ><a href="research.html" class="active">Overview</a></li>
<li><a href="mmsbl.html">Multimodal Sparse Bayesian Dictionary Learning Applied to Multimodal Data Classification</a></li>
<li><a href="facerecognition.html">Robust Bayesian Simultaneous Block Sparse Signal Recovery with Applications to Face Recognition</a></li>
<li><a href="nmf.html">Unified Bayesian Approach to Non-Negative Matrix Factorization</a></li>
<li class="active"><a href="rsbl.html">Rectified Sparse Bayesian Learning</a></li>
<li><a href="speechdenoising.html">Speech Denoising Headset</a></li>
<li><a href="DepthVideoCompression.html">Kinect Depth Video Compression for Action Recognition</a></li>
<li><a href="Construction.html">Construction Worker Activity Recognition Using RGB-D Videos</a></li>
</ul>
</li>
<li role="" ><a href="publications.html">Publications</a></li>
<li role="" ><a href="grants.html">Grants/Awards</a></li>
<li role="" ><a href="resumeNew.pdf">CV</a></li>
</ul>
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<div class="container">
<h1> Igor Fedorov </h1>
<div class="container row-md-4">
<div class="container col-md-12 col-sm-12 row-md-offset-2">
<h2> Rectified Sparse Bayesian Learning</h2>
The goal of this work is to solve the sparse non-negative least squares problem
$$ \text{argmin} \Vert y - \Phi x \Vert_2^2 \; \; \text{subject to} \; \; x \geq 0, \Vert x \Vert_0 \leq L $$
We extend the Sparse Bayesian Learning (SBL) framework used in Bayesian sparse signal recovery to non-negative signals. We investigate rectified Gaussian (RG) scale mixtures as a viable sparsity enforicing prior and develop efficient inference techniques.
</div>
</div>
<div class="container row-md-4 row-md-offset-2">
<div class="container col-md-12 col-sm-12">
<h3> Relevant Publications </h3>
<ul class="list-unstyled">
<li>A. Nalci, <em><b>I. Fedorov</em></b>, B.D. Rao, <a href="http://arxiv.org/abs/1601.06207" rel="nofollow">"Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem,"</a> <em>arXiv preprint arXiv:1601.06207</em>, 2016.</li>
</ul>
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<body>
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