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#invariance

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Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #239 Why Full, Partial, or Approximate Measurement Invariance Are Not a Prerequisite for Meaningful and Valid Group Comparisons</p><p>Thoughts: Item loadings should be the same across groups. This is v important &amp; also ok if not 🤷🏼‍♂️</p><p><a href="https://mastodon.social/tags/psychometrics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychometrics</span></a> <a href="https://mastodon.social/tags/variance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>variance</span></a> <a href="https://mastodon.social/tags/itemloading" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>itemloading</span></a> <a href="https://mastodon.social/tags/invariance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>invariance</span></a> </p><p><a href="https://www.tandfonline.com/doi/full/10.1080/10705511.2023.2191292" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">tandfonline.com/doi/full/10.10</span><span class="invisible">80/10705511.2023.2191292</span></a></p>
Dennis Alexis Valin Dittrich<p>Interpolation Can Provably Preclude Invariance <a href="https://arxiv.org/abs/2211.15724" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2211.15724</span><span class="invisible"></span></a><br><a href="https://fediscience.org/tags/Overfitting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Overfitting</span></a> to the point of <a href="https://fediscience.org/tags/interpolation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>interpolation</span></a> can hinder invariance-inducing objectives: One cannot assume a <a href="https://fediscience.org/tags/DeepLearninig" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepLearninig</span></a> model with an invariance penalty will indeed achieve any form of <a href="https://fediscience.org/tags/invariance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>invariance</span></a>… suggests that “benign overfitting,” in which models generalize well despite interpolating, might not favorably extend to settings in which <a href="https://fediscience.org/tags/robustness" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>robustness</span></a> or <a href="https://fediscience.org/tags/fairness" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fairness</span></a> are desirable.</p>
Yohan John 🤖🧠<p>"By definition, only amodal properties (information not specific to a particular sensory system; e.g., tempo, rhythm, duration, intensity) can be redundantly specified across the senses."</p><p>In other words, cross-modal redundancy is a type of invariance or symmetry with respect to transformation of sensory modality.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4316375/" rel="nofollow noopener" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">ncbi.nlm.nih.gov/pmc/articles/</span><span class="invisible">PMC4316375/</span></a></p><p>🧵 More excerpts below 👇 </p><p><a href="https://fediscience.org/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neuroscience</span></a> <a href="https://fediscience.org/tags/Psychology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Psychology</span></a> <a href="https://fediscience.org/tags/Attention" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Attention</span></a> <a href="https://fediscience.org/tags/Invariance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Invariance</span></a> <a href="https://fediscience.org/tags/Symmetry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Symmetry</span></a></p>
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