<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.10.0">Jekyll</generator><link href="https://proceedings.mlr.press/v313/feed.xml" rel="self" type="application/atom+xml" /><link href="https://proceedings.mlr.press/v313/" rel="alternate" type="text/html" /><updated>2026-05-05T08:43:03+00:00</updated><id>https://proceedings.mlr.press/v313/feed.xml</id><title type="html">Proceedings of Machine Learning Research</title><subtitle>Proceedings of The 37th International Conference on Algorithmic Learning Theory
  Held in Fields Institute, Toronto, Canada on 23-26 February 2026

Published as Volume 313 by the Proceedings of Machine Learning Research on 05 May 2026.

Volume Edited by:
  Matus Telgarsky
  Jonathan Ullman

Series Editors:
  Neil D. Lawrence
</subtitle><author><name>PMLR</name></author><entry><title type="html">Efficient and Provable Algorithms for Covariate Shift</title><link href="https://proceedings.mlr.press/v313/adil26a.html" rel="alternate" type="text/html" title="Efficient and Provable Algorithms for Covariate Shift" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/adil26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/adil26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Deeksha&quot;, &quot;family&quot;=&gt;&quot;Adil&quot;}, {&quot;given&quot;=&gt;&quot;Jaroslaw&quot;, &quot;family&quot;=&gt;&quot;Blasiok&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Convex optimization with $p$-norm oracles</title><link href="https://proceedings.mlr.press/v313/adil26b.html" rel="alternate" type="text/html" title="Convex optimization with $p$-norm oracles" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/adil26b</id><content type="html" xml:base="https://proceedings.mlr.press/v313/adil26b.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Deeksha&quot;, &quot;family&quot;=&gt;&quot;Adil&quot;}, {&quot;given&quot;=&gt;&quot;Brian&quot;, &quot;family&quot;=&gt;&quot;Bullins&quot;}, {&quot;given&quot;=&gt;&quot;Arun&quot;, &quot;family&quot;=&gt;&quot;Jambulapati&quot;}, {&quot;given&quot;=&gt;&quot;Aaron&quot;, &quot;family&quot;=&gt;&quot;Sidford&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data</title><link href="https://proceedings.mlr.press/v313/agrawal26a.html" rel="alternate" type="text/html" title="Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/agrawal26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/agrawal26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Shubhada&quot;, &quot;family&quot;=&gt;&quot;Agrawal&quot;}, {&quot;given&quot;=&gt;&quot;Aaditya&quot;, &quot;family&quot;=&gt;&quot;Ramdas&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Learning from Synthetic Data: Limitations of ERM</title><link href="https://proceedings.mlr.press/v313/amin26a.html" rel="alternate" type="text/html" title="Learning from Synthetic Data: Limitations of ERM" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/amin26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/amin26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Kareem&quot;, &quot;family&quot;=&gt;&quot;Amin&quot;}, {&quot;given&quot;=&gt;&quot;Alex&quot;, &quot;family&quot;=&gt;&quot;Bie&quot;}, {&quot;given&quot;=&gt;&quot;Weiwei&quot;, &quot;family&quot;=&gt;&quot;Kong&quot;}, {&quot;given&quot;=&gt;&quot;Umar&quot;, &quot;family&quot;=&gt;&quot;Syed&quot;}, {&quot;given&quot;=&gt;&quot;Sergei&quot;, &quot;family&quot;=&gt;&quot;Vassilvitskii&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Group-realizable multi-group learning by minimizing empirical risk</title><link href="https://proceedings.mlr.press/v313/ardeshir26a.html" rel="alternate" type="text/html" title="Group-realizable multi-group learning by minimizing empirical risk" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/ardeshir26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/ardeshir26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Navid&quot;, &quot;family&quot;=&gt;&quot;Ardeshir&quot;}, {&quot;given&quot;=&gt;&quot;Samuel&quot;, &quot;family&quot;=&gt;&quot;Deng&quot;}, {&quot;given&quot;=&gt;&quot;Daniel&quot;, &quot;family&quot;=&gt;&quot;Hsu&quot;}, {&quot;given&quot;=&gt;&quot;Jingwen&quot;, &quot;family&quot;=&gt;&quot;Liu&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Robust Online Learning</title><link href="https://proceedings.mlr.press/v313/ashkezari26a.html" rel="alternate" type="text/html" title="Robust Online Learning" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/ashkezari26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/ashkezari26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Sajad&quot;, &quot;family&quot;=&gt;&quot;Ashkezari&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">On the Hardness of Learning Regular Expressions</title><link href="https://proceedings.mlr.press/v313/attias26a.html" rel="alternate" type="text/html" title="On the Hardness of Learning Regular Expressions" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/attias26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/attias26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Idan&quot;, &quot;family&quot;=&gt;&quot;Attias&quot;}, {&quot;given&quot;=&gt;&quot;Lev&quot;, &quot;family&quot;=&gt;&quot;Reyzin&quot;}, {&quot;given&quot;=&gt;&quot;Nathan&quot;, &quot;family&quot;=&gt;&quot;Srebro&quot;}, {&quot;given&quot;=&gt;&quot;Gal&quot;, &quot;family&quot;=&gt;&quot;Vardi&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Reward Selection with Noisy Observations</title><link href="https://proceedings.mlr.press/v313/azizzadenesheli26a.html" rel="alternate" type="text/html" title="Reward Selection with Noisy Observations" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/azizzadenesheli26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/azizzadenesheli26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Kamyar&quot;, &quot;family&quot;=&gt;&quot;Azizzadenesheli&quot;}, {&quot;given&quot;=&gt;&quot;Trung&quot;, &quot;family&quot;=&gt;&quot;Dang&quot;}, {&quot;given&quot;=&gt;&quot;Aranyak&quot;, &quot;family&quot;=&gt;&quot;Mehta&quot;}, {&quot;given&quot;=&gt;&quot;Alexandros&quot;, &quot;family&quot;=&gt;&quot;Psomas&quot;}, {&quot;given&quot;=&gt;&quot;Qian&quot;, &quot;family&quot;=&gt;&quot;Zhang&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Discriminative Feature Feedback with General Teacher Classes</title><link href="https://proceedings.mlr.press/v313/bar-oz26a.html" rel="alternate" type="text/html" title="Discriminative Feature Feedback with General Teacher Classes" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/bar-oz26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/bar-oz26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Omri&quot;, &quot;family&quot;=&gt;&quot;Bar Oz&quot;}, {&quot;given&quot;=&gt;&quot;Tosca&quot;, &quot;family&quot;=&gt;&quot;Lechner&quot;}, {&quot;given&quot;=&gt;&quot;Sivan&quot;, &quot;family&quot;=&gt;&quot;Sabato&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Predictive inference for time series: why is split conformal effective despite temporal dependence?</title><link href="https://proceedings.mlr.press/v313/barber26a.html" rel="alternate" type="text/html" title="Predictive inference for time series: why is split conformal effective despite temporal dependence?" /><published>2026-05-05T00:00:00+00:00</published><updated>2026-05-05T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v313/barber26a</id><content type="html" xml:base="https://proceedings.mlr.press/v313/barber26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Rina Foygel&quot;, &quot;family&quot;=&gt;&quot;Barber&quot;}, {&quot;given&quot;=&gt;&quot;Ashwin&quot;, &quot;family&quot;=&gt;&quot;Pananjady&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry></feed>