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#encoders

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JMLR<p>&#39;White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?&#39;, by Yaodong Yu et al.</p><p><a href="http://jmlr.org/papers/v25/23-1547.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/23-1547.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/compressive" class="mention hashtag" rel="tag">#<span>compressive</span></a> <a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a></p>
JMLR<p>&#39;Studying the Interplay between Information Loss and Operation Loss in Representations for Classification&#39;, by Jorge F. Silva, Felipe Tobar, Mario Vicuña, Felipe Cordova.</p><p><a href="http://jmlr.org/papers/v25/21-1551.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/21-1551.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a> <a href="https://sigmoid.social/tags/lossless" class="mention hashtag" rel="tag">#<span>lossless</span></a> <a href="https://sigmoid.social/tags/informational" class="mention hashtag" rel="tag">#<span>informational</span></a></p>
PrivacyDigest<p>How <a href="https://mas.to/tags/Hackers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Hackers</span></a> Extracted the ‘Keys to the Kingdom’ to Clone <a href="https://mas.to/tags/HID" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HID</span></a> <a href="https://mas.to/tags/Keycards" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Keycards</span></a> </p><p>A team of researchers have developed a method for extracting <a href="https://mas.to/tags/authentication" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>authentication</span></a> keys out of HID <a href="https://mas.to/tags/encoders" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>encoders</span></a>, which could allow hackers to <a href="https://mas.to/tags/clone" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>clone</span></a> the types of keycards used to secure offices and other areas worldwide.<br><a href="https://mas.to/tags/security" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>security</span></a></p><p><a href="https://www.wired.com/story/hid-keycard-authentication-key-vulnerability/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">wired.com/story/hid-keycard-au</span><span class="invisible">thentication-key-vulnerability/</span></a></p>
New Submissions to TMLR<p>Relating graph auto-encoders to linear models</p><p><a href="https://openreview.net/forum?id=Y1eYplvxrE" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=Y1eYpl</span><span class="invisible">vxrE</span></a></p><p><a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a> <a href="https://sigmoid.social/tags/embedding" class="mention hashtag" rel="tag">#<span>embedding</span></a> <a href="https://sigmoid.social/tags/encoder" class="mention hashtag" rel="tag">#<span>encoder</span></a></p>
Published papers at TMLR<p>EdiBERT: a generative model for image editing</p><p>Thibaut Issenhuth, Ugo Tanielian, Jeremie Mary, David Picard</p><p><a href="https://openreview.net/forum?id=GRBbtkW3Lp" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=GRBbtk</span><span class="invisible">W3Lp</span></a></p><p><a href="https://sigmoid.social/tags/generative" class="mention hashtag" rel="tag">#<span>generative</span></a> <a href="https://sigmoid.social/tags/gans" class="mention hashtag" rel="tag">#<span>gans</span></a> <a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a></p>
TMLR certifications<p>New <a href="https://sigmoid.social/tags/FeaturedCertification" class="mention hashtag" rel="tag">#<span>FeaturedCertification</span></a>:</p><p>On Characterizing the Trade-off in Invariant Representation Learning</p><p>Bashir Sadeghi, Sepehr Dehdashtian, Vishnu Boddeti</p><p><a href="https://openreview.net/forum?id=3gfpBR1ncr" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=3gfpBR</span><span class="invisible">1ncr</span></a></p><p><a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a> <a href="https://sigmoid.social/tags/representation" class="mention hashtag" rel="tag">#<span>representation</span></a> <a href="https://sigmoid.social/tags/encoder" class="mention hashtag" rel="tag">#<span>encoder</span></a></p>
Published papers at TMLR<p>On Characterizing the Trade-off in Invariant Representation Learning</p><p>Bashir Sadeghi, Sepehr Dehdashtian, Vishnu Boddeti</p><p><a href="https://openreview.net/forum?id=3gfpBR1ncr" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=3gfpBR</span><span class="invisible">1ncr</span></a></p><p><a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a> <a href="https://sigmoid.social/tags/representation" class="mention hashtag" rel="tag">#<span>representation</span></a> <a href="https://sigmoid.social/tags/encoder" class="mention hashtag" rel="tag">#<span>encoder</span></a></p>
Published papers at TMLR<p>Unsupervised Learning of Neurosymbolic Encoders</p><p>Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri</p><p><a href="https://openreview.net/forum?id=eWvBEMTlRq" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=eWvBEM</span><span class="invisible">TlRq</span></a></p><p><a href="https://sigmoid.social/tags/encoders" class="mention hashtag" rel="tag">#<span>encoders</span></a> <a href="https://sigmoid.social/tags/representations" class="mention hashtag" rel="tag">#<span>representations</span></a> <a href="https://sigmoid.social/tags/encoder" class="mention hashtag" rel="tag">#<span>encoder</span></a></p>
smwinn7_runs<p><a href="https://mastodon.social/tags/introductionpost" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introductionpost</span></a> <a href="https://mastodon.social/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a> <br>Hello fediverse looking forward to finding other <a href="https://mastodon.social/tags/runner" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>runner</span></a> <a href="https://mastodon.social/tags/cyclist" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cyclist</span></a> <a href="https://mastodon.social/tags/zwift" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>zwift</span></a> interested people. I spend my days working to help <a href="https://mastodon.social/tags/automationindustry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>automationindustry</span></a> <a href="https://mastodon.social/tags/iec61131" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>iec61131</span></a> <a href="https://mastodon.social/tags/ethercat" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ethercat</span></a> <a href="https://mastodon.social/tags/motioncontrol" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>motioncontrol</span></a> mostly work with <a href="https://mastodon.social/tags/encoders" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>encoders</span></a> currently working with anyone that needs precision motion feedback</p><p>Looking forward to expanding my connections here.</p>
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