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#distributional

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JMLR<p>&#39;Unsupervised Tree Boosting for Learning Probability Distributions&#39;, by Naoki Awaya, Li Ma.</p><p><a href="http://jmlr.org/papers/v25/22-0980.html" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/22-0980.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/boosting" class="mention hashtag" rel="tag">#<span>boosting</span></a> <a href="https://sigmoid.social/tags/ensembles" class="mention hashtag" rel="tag">#<span>ensembles</span></a> <a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a></p>
Published papers at TMLR<p>The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning</p><p>Ludvig Killingberg, Helge Langseth</p><p>Action editor: Amir-massoud Farahmand.</p><p><a href="https://openreview.net/forum?id=z49eaB8kiH" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=z49eaB</span><span class="invisible">8kiH</span></a></p><p><a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a> <a href="https://sigmoid.social/tags/reinforcement" class="mention hashtag" rel="tag">#<span>reinforcement</span></a> <a href="https://sigmoid.social/tags/distributions" class="mention hashtag" rel="tag">#<span>distributions</span></a></p>
Published papers at TMLR<p>One-Step Distributional Reinforcement Learning</p><p>Mastane Achab, Reda ALAMI, YASSER ABDELAZIZ DAHOU DJILALI, Kirill Fedyanin, Eric Moulines</p><p>Action editor: Marc Lanctot.</p><p><a href="https://openreview.net/forum?id=ZPMf53vE1L" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=ZPMf53</span><span class="invisible">vE1L</span></a></p><p><a href="https://sigmoid.social/tags/reinforcement" class="mention hashtag" rel="tag">#<span>reinforcement</span></a> <a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a> <a href="https://sigmoid.social/tags/agent" class="mention hashtag" rel="tag">#<span>agent</span></a></p>
New Submissions to TMLR<p>The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning</p><p><a href="https://openreview.net/forum?id=z49eaB8kiH" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=z49eaB</span><span class="invisible">8kiH</span></a></p><p><a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a> <a href="https://sigmoid.social/tags/reinforcement" class="mention hashtag" rel="tag">#<span>reinforcement</span></a> <a href="https://sigmoid.social/tags/distributions" class="mention hashtag" rel="tag">#<span>distributions</span></a></p>
Published papers at TMLR<p>Empirical Study on Optimizer Selection for Out-of-Distribution Generalization</p><p>Hiroki Naganuma, Kartik Ahuja, Shiro Takagi et al.</p><p>Action editor: Robert Gower.</p><p><a href="https://openreview.net/forum?id=ipe0IMglFF" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=ipe0IM</span><span class="invisible">glFF</span></a></p><p><a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a> <a href="https://sigmoid.social/tags/generalization" class="mention hashtag" rel="tag">#<span>generalization</span></a> <a href="https://sigmoid.social/tags/classification" class="mention hashtag" rel="tag">#<span>classification</span></a></p>
New Submissions to TMLR<p>Empirical Study on Optimizer Selection for Out-of-Distribution Generalization</p><p><a href="https://openreview.net/forum?id=ipe0IMglFF" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=ipe0IM</span><span class="invisible">glFF</span></a></p><p><a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a> <a href="https://sigmoid.social/tags/generalization" class="mention hashtag" rel="tag">#<span>generalization</span></a> <a href="https://sigmoid.social/tags/classification" class="mention hashtag" rel="tag">#<span>classification</span></a></p>
Published papers at TMLR<p>How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts</p><p>Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang</p><p><a href="https://openreview.net/forum?id=11pGlecTz2" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=11pGle</span><span class="invisible">cTz2</span></a></p><p><a href="https://sigmoid.social/tags/fairness" class="mention hashtag" rel="tag">#<span>fairness</span></a> <a href="https://sigmoid.social/tags/minority" class="mention hashtag" rel="tag">#<span>minority</span></a> <a href="https://sigmoid.social/tags/distributional" class="mention hashtag" rel="tag">#<span>distributional</span></a></p>
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