<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Regularisation on Mohamad H. Danesh</title><link>https://modanesh.github.io/tags/regularisation/</link><description>Recent content in Regularisation on Mohamad H. Danesh</description><generator>Hugo -- 0.147.2</generator><language>en</language><lastBuildDate>Wed, 07 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://modanesh.github.io/tags/regularisation/index.xml" rel="self" type="application/rss+xml"/><item><title>Regularised RL Improves Sim-to-Real Transfer</title><link>https://modanesh.github.io/papers/smm/</link><pubDate>Wed, 07 Oct 2026 00:00:00 +0000</pubDate><guid>https://modanesh.github.io/papers/smm/</guid><description>SMM-AC extends the soft mellowmax value function to continuous control. On real Franka and ANYmal-D robots it transfers better from simulation and keeps more of its return under deployment-time perturbations than PPO, FastTD3, and SAC.</description></item></channel></rss>