<?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/v306/feed.xml" rel="self" type="application/atom+xml" /><link href="https://proceedings.mlr.press/v306/" rel="alternate" type="text/html" /><updated>2026-09-29T07:02:12+00:00</updated><id>https://proceedings.mlr.press/v306/feed.xml</id><title type="html">Proceedings of Machine Learning Research</title><subtitle>Proceedings of the 43rd International Conference on Machine Learning
  Held in Seoul, South Korea on 06-11 July 2026

Published as Volume 306 by the Proceedings of Machine Learning Research on 29 September 2026.

Volume Edited by:
  Tong Zhang
  Miroslav Dudik
  Martin Jaggi
  Alekh Agarwal
  Sharon Li
  Dale Schuurmans
  Jerry Zhu
  Felix Berkenkamp
  Hanze Dong
  Alberto Bietti

Series Editors:
  Tegan Emerson
  Hoel Kervadec
  Neil D. Lawrence
</subtitle><author><name>PMLR</name></author><entry><title type="html">TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization</title><link href="https://proceedings.mlr.press/v306/abas26a.html" rel="alternate" type="text/html" title="TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abas26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abas26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Abdulhady&quot;, &quot;family&quot;=&gt;&quot;Abas&quot;}, {&quot;given&quot;=&gt;&quot;Fatemeh&quot;, &quot;family&quot;=&gt;&quot;Daneshfar&quot;}, {&quot;given&quot;=&gt;&quot;Seyedali&quot;, &quot;family&quot;=&gt;&quot;Mirjalili&quot;}, {&quot;given&quot;=&gt;&quot;Mourad&quot;, &quot;family&quot;=&gt;&quot;Oussalah&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">What Preferences Can—and Cannot—Predict in Multi-Agent Online Learning</title><link href="https://proceedings.mlr.press/v306/abbadi26a.html" rel="alternate" type="text/html" title="What Preferences Can—and Cannot—Predict in Multi-Agent Online Learning" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abbadi26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abbadi26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Omar&quot;, &quot;family&quot;=&gt;&quot;Abbadi&quot;}, {&quot;given&quot;=&gt;&quot;Rida&quot;, &quot;family&quot;=&gt;&quot;Laraki&quot;}, {&quot;given&quot;=&gt;&quot;Panayotis&quot;, &quot;family&quot;=&gt;&quot;Mertikopoulos&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses</title><link href="https://proceedings.mlr.press/v306/abbas26a.html" rel="alternate" type="text/html" title="QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abbas26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abbas26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Amira&quot;, &quot;family&quot;=&gt;&quot;Abbas&quot;}, {&quot;given&quot;=&gt;&quot;Yanlin&quot;, &quot;family&quot;=&gt;&quot;Chen&quot;}, {&quot;given&quot;=&gt;&quot;Tuyen Quang&quot;, &quot;family&quot;=&gt;&quot;Nguyen&quot;}, {&quot;given&quot;=&gt;&quot;Ronald&quot;, &quot;family&quot;=&gt;&quot;De Wolf&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression</title><link href="https://proceedings.mlr.press/v306/abbasi26a.html" rel="alternate" type="text/html" title="Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abbasi26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abbasi26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Ali&quot;, &quot;family&quot;=&gt;&quot;Abbasi&quot;}, {&quot;given&quot;=&gt;&quot;Chayne&quot;, &quot;family&quot;=&gt;&quot;Thrash&quot;}, {&quot;given&quot;=&gt;&quot;Haoran&quot;, &quot;family&quot;=&gt;&quot;Qin&quot;}, {&quot;given&quot;=&gt;&quot;Shansita&quot;, &quot;family&quot;=&gt;&quot;Sharma&quot;}, {&quot;given&quot;=&gt;&quot;Sepehr&quot;, &quot;family&quot;=&gt;&quot;Seifi&quot;}, {&quot;given&quot;=&gt;&quot;Soheil&quot;, &quot;family&quot;=&gt;&quot;Kolouri&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">MODEL SOUPS NEED ONLY ONE INGREDIENT</title><link href="https://proceedings.mlr.press/v306/abdollahpoorrostam26a.html" rel="alternate" type="text/html" title="MODEL SOUPS NEED ONLY ONE INGREDIENT" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abdollahpoorrostam26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abdollahpoorrostam26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Alireza&quot;, &quot;family&quot;=&gt;&quot;Abdollahpoorrostam&quot;}, {&quot;given&quot;=&gt;&quot;Nikolaos&quot;, &quot;family&quot;=&gt;&quot;Dimitriadis&quot;}, {&quot;given&quot;=&gt;&quot;Adam&quot;, &quot;family&quot;=&gt;&quot;Hazimeh&quot;}, {&quot;given&quot;=&gt;&quot;Pascal&quot;, &quot;family&quot;=&gt;&quot;Frossard&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Concept Heterogeneity-aware Representation Steering</title><link href="https://proceedings.mlr.press/v306/abdullaev26a.html" rel="alternate" type="text/html" title="Concept Heterogeneity-aware Representation Steering" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abdullaev26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abdullaev26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Laziz&quot;, &quot;family&quot;=&gt;&quot;Abdullaev&quot;}, {&quot;given&quot;=&gt;&quot;Noelle Y. L.&quot;, &quot;family&quot;=&gt;&quot;Wong&quot;}, {&quot;given&quot;=&gt;&quot;Ryan Lee T.&quot;, &quot;family&quot;=&gt;&quot;Z.&quot;}, {&quot;given&quot;=&gt;&quot;Shiqi&quot;, &quot;family&quot;=&gt;&quot;Jiang&quot;}, {&quot;given&quot;=&gt;&quot;Minh-Khoi&quot;, &quot;family&quot;=&gt;&quot;Nguyen-Nhat&quot;}, {&quot;given&quot;=&gt;&quot;Tan Minh&quot;, &quot;family&quot;=&gt;&quot;Nguyen&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization</title><link href="https://proceedings.mlr.press/v306/abe26a.html" rel="alternate" type="text/html" title="Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abe26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abe26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Kenshi&quot;, &quot;family&quot;=&gt;&quot;Abe&quot;}, {&quot;given&quot;=&gt;&quot;Mitsuki&quot;, &quot;family&quot;=&gt;&quot;Sakamoto&quot;}, {&quot;given&quot;=&gt;&quot;Kaito&quot;, &quot;family&quot;=&gt;&quot;Ariu&quot;}, {&quot;given&quot;=&gt;&quot;Atsushi&quot;, &quot;family&quot;=&gt;&quot;Iwasaki&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Physics-Informed Residual Flows</title><link href="https://proceedings.mlr.press/v306/abijuru26a.html" rel="alternate" type="text/html" title="Physics-Informed Residual Flows" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abijuru26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abijuru26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Jephte&quot;, &quot;family&quot;=&gt;&quot;Abijuru&quot;}, {&quot;given&quot;=&gt;&quot;Mayank&quot;, &quot;family&quot;=&gt;&quot;Nagda&quot;}, {&quot;given&quot;=&gt;&quot;Phil&quot;, &quot;family&quot;=&gt;&quot;Ostheimer&quot;}, {&quot;given&quot;=&gt;&quot;Sebastian Josef&quot;, &quot;family&quot;=&gt;&quot;Vollmer&quot;}, {&quot;given&quot;=&gt;&quot;Marius&quot;, &quot;family&quot;=&gt;&quot;Kloft&quot;}, {&quot;given&quot;=&gt;&quot;Sophie&quot;, &quot;family&quot;=&gt;&quot;Fellenz&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Heavy-tailed Physics-Informed Neural Networks</title><link href="https://proceedings.mlr.press/v306/abijuru26b.html" rel="alternate" type="text/html" title="Heavy-tailed Physics-Informed Neural Networks" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abijuru26b</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abijuru26b.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Jephte&quot;, &quot;family&quot;=&gt;&quot;Abijuru&quot;}, {&quot;given&quot;=&gt;&quot;Mayank&quot;, &quot;family&quot;=&gt;&quot;Nagda&quot;}, {&quot;given&quot;=&gt;&quot;Jan&quot;, &quot;family&quot;=&gt;&quot;Tauberschmidt&quot;}, {&quot;given&quot;=&gt;&quot;Phil&quot;, &quot;family&quot;=&gt;&quot;Ostheimer&quot;}, {&quot;given&quot;=&gt;&quot;Sebastian Josef&quot;, &quot;family&quot;=&gt;&quot;Vollmer&quot;}, {&quot;given&quot;=&gt;&quot;Stephan&quot;, &quot;family&quot;=&gt;&quot;Mandt&quot;}, {&quot;given&quot;=&gt;&quot;Marius&quot;, &quot;family&quot;=&gt;&quot;Kloft&quot;}, {&quot;given&quot;=&gt;&quot;Sophie&quot;, &quot;family&quot;=&gt;&quot;Fellenz&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding</title><link href="https://proceedings.mlr.press/v306/abramovich26a.html" rel="alternate" type="text/html" title="SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding" /><published>2026-09-29T00:00:00+00:00</published><updated>2026-09-29T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v306/abramovich26a</id><content type="html" xml:base="https://proceedings.mlr.press/v306/abramovich26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Talor&quot;, &quot;family&quot;=&gt;&quot;Abramovich&quot;}, {&quot;given&quot;=&gt;&quot;Maor&quot;, &quot;family&quot;=&gt;&quot;Ashkenazi&quot;}, {&quot;given&quot;=&gt;&quot;Izzy&quot;, &quot;family&quot;=&gt;&quot;Putterman&quot;}, {&quot;given&quot;=&gt;&quot;Benjamin&quot;, &quot;family&quot;=&gt;&quot;Chislett&quot;}, {&quot;given&quot;=&gt;&quot;Tiyasa&quot;, &quot;family&quot;=&gt;&quot;Mitra&quot;}, {&quot;given&quot;=&gt;&quot;Bita&quot;, &quot;family&quot;=&gt;&quot;Darvish Rouhani&quot;}, {&quot;given&quot;=&gt;&quot;Ran&quot;, &quot;family&quot;=&gt;&quot;Zilberstein&quot;}, {&quot;given&quot;=&gt;&quot;Yonatan&quot;, &quot;family&quot;=&gt;&quot;Geifman&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry></feed>