<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: lyelibi</title><link>https://news.ycombinator.com/user?id=lyelibi</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sat, 07 Nov 2026 17:18:07 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=lyelibi" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by lyelibi in "Tesla to wind down Cybertruck production"]]></title><description><![CDATA[
<p>You're dismissing a cultural aspect of the popularity of trucks in america. There is way more trucks in Texas than say in Indiana, or Massachusetts on the road. Texas is one of the only states where people still drive hummers. They're not all doing off-roads</p>
]]></description><pubDate>Fri, 06 Nov 2026 16:26:50 +0000</pubDate><link>https://news.ycombinator.com/item?id=50394486</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=50394486</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50394486</guid></item><item><title><![CDATA[New comment by lyelibi in "TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14"]]></title><description><![CDATA[
<p>The issue is with the framing, the justification for the added overhead in training and productionalizing deep learning models is to take advantage of scaling laws: If you have more compute, and more data you should get better performance especially over xgboost architectures. So if we are to take what you said seriously it's even less reasons to invest in tabular transformers.</p>
]]></description><pubDate>Tue, 29 Sep 2026 00:22:50 +0000</pubDate><link>https://news.ycombinator.com/item?id=49886311</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=49886311</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49886311</guid></item><item><title><![CDATA[New comment by lyelibi in "TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14"]]></title><description><![CDATA[
<p>I have never seen tabular transformer models beat xgboost/catboost in industrial context where datasets is gigantic. They most produce these results on relatively small datasets, clearly not in the tens of millions of rows.</p>
]]></description><pubDate>Mon, 28 Sep 2026 05:49:27 +0000</pubDate><link>https://news.ycombinator.com/item?id=49874109</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=49874109</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49874109</guid></item><item><title><![CDATA[New comment by lyelibi in "Fourier Transforms"]]></title><description><![CDATA[
<p>It's not just curve fitting because basis functions have characteristics which make them desirable for the kind of decomposition one is trying to find. We typically assume in factor analysis that factors are gaussian random variables without clear and repeating patterns. Fourrier transforms force us to think in similar terms but accounting for specific dynamics factor (I. E. Basis functions) should capture.<p>Also how do we construct those orthogonal basis functions for any downstream task is an interesting research question!</p>
]]></description><pubDate>Sun, 16 Nov 2025 19:03:29 +0000</pubDate><link>https://news.ycombinator.com/item?id=45947485</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=45947485</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45947485</guid></item><item><title><![CDATA[New comment by lyelibi in "Ask HN: Who is hiring? (December 2024)"]]></title><description><![CDATA[
<p>seems broken, at least the ML role</p>
]]></description><pubDate>Tue, 10 Dec 2024 22:55:56 +0000</pubDate><link>https://news.ycombinator.com/item?id=42382620</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=42382620</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42382620</guid></item><item><title><![CDATA[New comment by lyelibi in "Ask HN: Who wants to be hired? (December 2024)"]]></title><description><![CDATA[
<p><p><pre><code>  Location: Houston, TX
  Remote: Yes
  Willing to relocate: No but can travel.
  Technologies: Python
  Résumé/CV: linkedin.com/in/lionelyelibi
  Email: yelibi@spincitylab.com
</code></pre>
I am a research scientist currently working in financial services. My background is in physics, data science and machine learning. I have broad interests so hit me to talk about your project ideas or your firm's mission. Over the last +8yrs I have worked as IC or lead in various academic and industrial research projects. I'm looking for a real challenge and a group of like-minded folks to build with.</p>
]]></description><pubDate>Mon, 02 Dec 2024 20:59:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=42300325</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=42300325</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42300325</guid></item><item><title><![CDATA[New comment by lyelibi in "Ask HN: Who is hiring? (November 2024)"]]></title><description><![CDATA[
<p>Hey, I'd like to know more on what you guys are looking to do. Do I DM on twitter?</p>
]]></description><pubDate>Tue, 05 Nov 2024 06:16:26 +0000</pubDate><link>https://news.ycombinator.com/item?id=42049005</link><dc:creator>lyelibi</dc:creator><comments>https://news.ycombinator.com/item?id=42049005</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42049005</guid></item></channel></rss>