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IT News<p>Watch Bondo Putty Get Sprayed Onto 3D Prints - 3D prints destined for presentation need smooth surfaces, and that usually means s... - <a href="https://hackaday.com/2025/08/31/watch-bondo-putty-get-sprayed-onto-3d-prints/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">hackaday.com/2025/08/31/watch-</span><span class="invisible">bondo-putty-get-sprayed-onto-3d-prints/</span></a> <a href="https://schleuss.online/tags/3dprinterhacks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>3dprinterhacks</span></a> <a href="https://schleuss.online/tags/toolhacks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>toolhacks</span></a> <a href="https://schleuss.online/tags/3dprinted" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>3dprinted</span></a> <a href="https://schleuss.online/tags/smoothing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>smoothing</span></a> <a href="https://schleuss.online/tags/airbrush" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>airbrush</span></a> <a href="https://schleuss.online/tags/acetone" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>acetone</span></a> <a href="https://schleuss.online/tags/sanding" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sanding</span></a> <a href="https://schleuss.online/tags/bondo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bondo</span></a></p>
JMLR<p>&#39;From Sparse to Dense Functional Data in High Dimensions: Revisiting Phase Transitions from a Non-Asymptotic Perspective&#39;, by Shaojun Guo, Dong Li, Xinghao Qiao, Yizhu Wang.</p><p><a href="http://jmlr.org/papers/v26/23-1578.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v26/23-1578.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/sparse" class="mention hashtag" rel="tag">#<span>sparse</span></a> <a href="https://sigmoid.social/tags/nonparametric" class="mention hashtag" rel="tag">#<span>nonparametric</span></a> <a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a></p>
JMLR<p>&#39;Efficient Active Manifold Identification via Accelerated Iteratively Reweighted Nuclear Norm Minimization&#39;, by Hao Wang, Ye Wang, Xiangyu Yang.</p><p><a href="http://jmlr.org/papers/v25/23-0449.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/23-0449.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/minimization" class="mention hashtag" rel="tag">#<span>minimization</span></a> <a href="https://sigmoid.social/tags/optimization" class="mention hashtag" rel="tag">#<span>optimization</span></a> <a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a></p>
JMLR<p>&#39;Random Smoothing Regularization in Kernel Gradient Descent Learning&#39;, by Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan Yao.</p><p><a href="http://jmlr.org/papers/v25/23-0580.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/23-0580.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/regularization" class="mention hashtag" rel="tag">#<span>regularization</span></a> <a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a> <a href="https://sigmoid.social/tags/gradient" class="mention hashtag" rel="tag">#<span>gradient</span></a></p>
AM<p><a href="https://mas.to/tags/art" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>art</span></a> <a href="https://mas.to/tags/generativeart" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>generativeart</span></a> <a href="https://mas.to/tags/process" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>process</span></a> <a href="https://mas.to/tags/digital" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>digital</span></a> <a href="https://mas.to/tags/alchemy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alchemy</span></a> <a href="https://mas.to/tags/code" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>code</span></a> <a href="https://mas.to/tags/smoothing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>smoothing</span></a> <a href="https://mas.to/tags/bug" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bug</span></a> 👁️</p>
JMLR<p>&#39;Functions with average smoothness: structure, algorithms, and learning&#39;, by Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich.</p><p><a href="http://jmlr.org/papers/v25/23-0182.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/23-0182.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a> <a href="https://sigmoid.social/tags/smoothness" class="mention hashtag" rel="tag">#<span>smoothness</span></a> <a href="https://sigmoid.social/tags/bounding" class="mention hashtag" rel="tag">#<span>bounding</span></a></p>
JMLR<p>&#39;Nonparametric Regression for 3D Point Cloud Learning&#39;, by Xinyi Li, Shan Yu, Yueying Wang, Guannan Wang, Li Wang, Ming-Jun Lai.</p><p><a href="http://jmlr.org/papers/v25/22-0735.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/22-0735.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a> <a href="https://sigmoid.social/tags/3d" class="mention hashtag" rel="tag">#<span>3d</span></a> <a href="https://sigmoid.social/tags/clouds" class="mention hashtag" rel="tag">#<span>clouds</span></a></p>
JMLR<p>&#39;Additive smoothing error in backward variational inference for general state-space models&#39;, by Mathis Chagneux, Elisabeth Gassiat, Pierre Gloaguen, Sylvain Le Corff.</p><p><a href="http://jmlr.org/papers/v25/22-1392.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/22-1392.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/variational" class="mention hashtag" rel="tag">#<span>variational</span></a> <a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a> <a href="https://sigmoid.social/tags/estimation" class="mention hashtag" rel="tag">#<span>estimation</span></a></p>
New Submissions to TMLR<p>Concert: Context-Aware Randomized Smoothing via Colorization-Based Entropy</p><p><a href="https://openreview.net/forum?id=Jy8VJTdIHy" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=Jy8VJT</span><span class="invisible">dIHy</span></a></p><p><a href="https://sigmoid.social/tags/adversarial" class="mention hashtag" rel="tag">#<span>adversarial</span></a> <a href="https://sigmoid.social/tags/robustness" class="mention hashtag" rel="tag">#<span>robustness</span></a> <a href="https://sigmoid.social/tags/smoothing" class="mention hashtag" rel="tag">#<span>smoothing</span></a></p>
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