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shubhangb97 committed Jun 16, 2024
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8 changes: 4 additions & 4 deletions MLR_gcn/index.html
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<a href="https://illinois.edu/">
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<a href="https://drive.google.com/file/d/1yqAci33Hi6S_MkdYLZ2XLV1--FYrACnq/view">
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<h4><strong>Workshop paper</strong></h4>
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<a href="https://arxiv.org/abs/2404.16193">
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<h4><strong>Extended Arxiv</strong></h4>
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<a href="img/MLR_GCN_poster.pdf">
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<h4><strong>Poster</strong></h4>
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<p align="justify"> <i id="PL_UDML_abs">Unsupervised deep metric learning (UDML) focuses on learning a semantic representation space
<p align="justify"> <i id="PL_UDML_abs"> Unsupervised deep metric learning (UDML) focuses on learning a semantic representation space
using only unlabeled data. This challenging problem requires accurately estimating the similarity between data points, which is used
to supervise a deep network. For this purpose, we propose to model the high-dimensional data manifold using a piecewise-linear
approximation, with each low-dimensional linear piece approximating the data manifold in a small neighborhood of a point.

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