diff --git a/assets/css/main.css b/assets/css/main.css
index d7b7f86f..9722364b 100644
--- a/assets/css/main.css
+++ b/assets/css/main.css
@@ -1,7 +1,8 @@
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diff --git a/assets/jupyter/blog.ipynb.html b/assets/jupyter/blog.ipynb.html
index 18746db2..53ea0034 100644
--- a/assets/jupyter/blog.ipynb.html
+++ b/assets/jupyter/blog.ipynb.html
@@ -1,4 +1,4 @@
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diff --git a/assets/jupyter/load_json.ipynb.html b/assets/jupyter/load_json.ipynb.html
index f0057bbb..8e130d02 100644
--- a/assets/jupyter/load_json.ipynb.html
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diff --git a/blog/2024/findvenue/index.html b/blog/2024/findvenue/index.html
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<header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="//"> <span class="font-weight-bold">Peter</span> Lorenz </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" 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class="post-tags"> <a href="//blog/2024"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </a>   ·   <a href="//blog/tag/icml"> <i class="fa-solid fa-hashtag fa-sm"></i> icml,</a>   <a href="//blog/tag/cvpr"> <i class="fa-solid fa-hashtag fa-sm"></i> cvpr,</a>   <a href="//blog/tag/conference"> <i class="fa-solid fa-hashtag fa-sm"></i> conference</a>   ·   <a href="//blog/category/writing"> <i class="fa-solid fa-tag fa-sm"></i> writing</a> </p> </header> <article class="post-content"> <div id="markdown-content"> <h1 id="how-do-you-find-your-conference-in-trustworthy-ml">How do you find your conference in trustworthy ML?</h1> <p>If you have finished doing your experiments, it is about finding the right venue.</p> <h2 id="via-google-ranking">Via Google Ranking</h2> <ul> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_artificialintelligence" rel="external nofollow noopener" target="_blank">Artificial Intelligence</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computervisionpatternrecognition" rel="external nofollow noopener" target="_blank">Computer Vision</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computationallinguistics" rel="external nofollow noopener" target="_blank">Computational Linguistics</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computersecuritycryptography" rel="external nofollow noopener" target="_blank">Security and Privacy</a></li> </ul> <p>The h-index and median are both metrics used to evaluate the impact of scholarly research publications, particularly in the field of academia.</p> <ol> <li> <p><strong>h-index</strong>: The h-index is a numerical value that attempts to measure both the productivity and impact of the published work of a scientist or scholar. It’s calculated based on the number of papers the researcher has published and the number of citations each paper has received. The h-index is determined by arranging the researcher’s publications according to the number of citations they have received. The h-index is the highest number of publications that have at least the same number of citations. For example, if a researcher has an h-index of 20, it means they have published at least 20 papers, each of which has been cited at least 20 times.</p> </li> <li> <p><strong>Median</strong>: In the context of h-index, the median is typically used to represent the median number of citations received by the researcher’s publications. This value provides insight into the central tendency of the citation distribution of the researcher’s work. It helps to understand the typical level of impact or recognition the researcher’s papers have received. If a researcher’s median citation count is high, it suggests that their publications tend to receive a substantial number of citations, indicating a significant impact in their field.</p> </li> </ol> <p>Both the h-index and median are valuable tools for evaluating the impact and significance of a researcher’s contributions, although they each capture slightly different aspects of the citation profile.</p> <h2 id="other-rankings">Other Rankings</h2> <ul> <li><a href="https://www.iiti.ac.in/people/~artiwari/cseconflist.html" rel="external nofollow noopener" target="_blank">CORE</a></li> <li><a href="http://www.conferenceranks.com" rel="external nofollow noopener" target="_blank">conference ranks</a></li> </ul> <h2 id="deadlines-tracking">Deadlines Tracking</h2> <ul> <li><a href="https://aideadlin.es/?sub=ML,CV,NLP,DM,KR" rel="external nofollow noopener" target="_blank">AI</a></li> <li><a href="https://sec-deadlines.github.io" rel="external nofollow noopener" target="_blank">SEC</a></li> <li><a href="https://iacr.org/events/?order=submission" rel="external nofollow noopener" target="_blank">IACR</a></li> </ul> <h2 id="other-recommended-conferences-and-workshops-for-trustworthy-ml">Other Recommended Conferences and Workshops for Trustworthy ML</h2> <ul> <li><a href="https://aisec.cc" rel="external nofollow noopener" target="_blank">ACM AISec</a></li> <li><a href="https://satml.org" rel="external nofollow noopener" target="_blank">IEEE SaTML</a></li> <li><a href="https://facctconference.org" rel="external nofollow noopener" target="_blank">ACM FAccT</a></li> </ul> <h2 id="research-trends">Research Trends</h2> <ul> <li><a href="https://colab.research.google.com/drive/1u51Id90ML79UdZaKD23qglY0ZkEmmdwk?usp=sharing#scrollTo=metallic-aquatic" rel="external nofollow noopener" target="_blank">NeurIPS keywords</a></li> <li><a href="https://public.tableau.com/app/profile/joshpreston/viz/CVPR2024/CVPRtrends" rel="external nofollow noopener" target="_blank">CVPR Trends</a></li> <li><a href="https://researchtrends.ai" rel="external nofollow noopener" target="_blank">Researchtrends.ai</a></li> <li><a href="https://medium.com/gptalk/llm-research-trends-from-17k-arxiv-papers-ed5dcc0fdb3d" rel="external nofollow noopener" target="_blank">LLM Research Trends</a></li> </ul> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra/">Google Gemini updates: Flash 1.5, Gemma 2 and Project Astra</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/how-to-write-a-good-scientific-review/">How to write a good scientific review?</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/habits/">Habits</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work/">Regulate your blood sugar! — Nourish to Flourish: Harnessing Glycogen for Peak Performance at Work</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/how-to-lead-when-you-are-not-in-charge/">How to lead when you are not in charge?</a> </li> <div id="giscus_thread" style="max-width: 930px; margin: 0 auto;"> <script>let giscusTheme=determineComputedTheme(),giscusAttributes={src:"https://giscus.app/client.js","data-repo":"lorenz-peter/lorenz-peter.github.io","data-repo-id":"","data-category":"Comments","data-category-id":"","data-mapping":"title","data-strict":"1","data-reactions-enabled":"1","data-emit-metadata":"0","data-input-position":"bottom","data-theme":giscusTheme,"data-lang":"en",crossorigin:"anonymous",async:""},giscusScript=document.createElement("script");Object.entries(giscusAttributes).forEach(([t,e])=>giscusScript.setAttribute(t,e)),document.getElementById("giscus_thread").appendChild(giscusScript);</script> <noscript>Please enable JavaScript to view the <a href="http://giscus.app/?ref_noscript" rel="external nofollow noopener" target="_blank">comments powered by giscus.</a> </noscript> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 Peter Lorenz. 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<header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="//"> <span class="font-weight-bold">Peter</span> Lorenz </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" 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class="post-tags"> <a href="//blog/2024"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </a>   ·   <a href="//blog/tag/icml"> <i class="fa-solid fa-hashtag fa-sm"></i> icml,</a>   <a href="//blog/tag/cvpr"> <i class="fa-solid fa-hashtag fa-sm"></i> cvpr,</a>   <a href="//blog/tag/conference"> <i class="fa-solid fa-hashtag fa-sm"></i> conference</a>   ·   <a href="//blog/category/writing"> <i class="fa-solid fa-tag fa-sm"></i> writing</a> </p> </header> <article class="post-content"> <div id="markdown-content"> <h1 id="how-do-you-find-your-conference-in-trustworthy-ml">How do you find your conference in trustworthy ML?</h1> <p>If you have finished doing your experiments, it is about finding the right venue.</p> <h2 id="via-google-ranking">Via Google Ranking</h2> <ul> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_artificialintelligence" rel="external nofollow noopener" target="_blank">Artificial Intelligence</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computervisionpatternrecognition" rel="external nofollow noopener" target="_blank">Computer Vision</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computationallinguistics" rel="external nofollow noopener" target="_blank">Computational Linguistics</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computersecuritycryptography" rel="external nofollow noopener" target="_blank">Security and Privacy</a></li> </ul> <p>The h-index and median are both metrics used to evaluate the impact of scholarly research publications, particularly in the field of academia.</p> <ol> <li> <p><strong>h-index</strong>: The h-index is a numerical value that attempts to measure both the productivity and impact of the published work of a scientist or scholar. It’s calculated based on the number of papers the researcher has published and the number of citations each paper has received. The h-index is determined by arranging the researcher’s publications according to the number of citations they have received. The h-index is the highest number of publications that have at least the same number of citations. For example, if a researcher has an h-index of 20, it means they have published at least 20 papers, each of which has been cited at least 20 times.</p> </li> <li> <p><strong>Median</strong>: In the context of h-index, the median is typically used to represent the median number of citations received by the researcher’s publications. This value provides insight into the central tendency of the citation distribution of the researcher’s work. It helps to understand the typical level of impact or recognition the researcher’s papers have received. If a researcher’s median citation count is high, it suggests that their publications tend to receive a substantial number of citations, indicating a significant impact in their field.</p> </li> </ol> <p>Both the h-index and median are valuable tools for evaluating the impact and significance of a researcher’s contributions, although they each capture slightly different aspects of the citation profile.</p> <h2 id="other-rankings">Other Rankings</h2> <ul> <li><a href="https://www.iiti.ac.in/people/~artiwari/cseconflist.html" rel="external nofollow noopener" target="_blank">CORE</a></li> <li><a href="http://www.conferenceranks.com" rel="external nofollow noopener" target="_blank">conference ranks</a></li> <li><a href="https://people.engr.tamu.edu/guofei/sec_conf_stat.htm" rel="external nofollow noopener" target="_blank">sec conf ranks</a></li> </ul> <h2 id="journals">Journals</h2> <p>One key difference between journal and conference publications is the review process. Journals typically involve a more thorough and time-consuming review process, with reviewers having more time to provide detailed feedback. As a result, the publication timeline for journals is often longer than for conferences.</p> <ul> <li><a href="https://en.wikipedia.org/wiki/IEEE_Transactions_on_Pattern_Analysis_and_Machine_Intelligence" rel="external nofollow noopener" target="_blank">TPAMI</a></li> </ul> <h2 id="deadlines-tracking">Deadlines Tracking</h2> <ul> <li><a href="https://aideadlin.es/?sub=ML,CV,NLP,DM,KR" rel="external nofollow noopener" target="_blank">AI</a></li> <li><a href="https://sec-deadlines.github.io" rel="external nofollow noopener" target="_blank">SEC</a></li> <li><a href="https://iacr.org/events/?order=submission" rel="external nofollow noopener" target="_blank">IACR</a></li> </ul> <h2 id="other-recommended-conferences-and-workshops-for-trustworthy-ml">Other Recommended Conferences and Workshops for Trustworthy ML</h2> <ul> <li><a href="https://aisec.cc" rel="external nofollow noopener" target="_blank">ACM AISec</a></li> <li><a href="https://satml.org" rel="external nofollow noopener" target="_blank">IEEE SaTML</a></li> <li><a href="https://facctconference.org" rel="external nofollow noopener" target="_blank">ACM FAccT</a></li> </ul> <h2 id="research-trends">Research Trends</h2> <ul> <li><a href="https://colab.research.google.com/drive/1u51Id90ML79UdZaKD23qglY0ZkEmmdwk?usp=sharing#scrollTo=metallic-aquatic" rel="external nofollow noopener" target="_blank">NeurIPS keywords</a></li> <li><a href="https://public.tableau.com/app/profile/joshpreston/viz/CVPR2024/CVPRtrends" rel="external nofollow noopener" target="_blank">CVPR Trends</a></li> <li><a href="https://researchtrends.ai" rel="external nofollow noopener" target="_blank">Researchtrends.ai</a></li> <li><a href="https://medium.com/gptalk/llm-research-trends-from-17k-arxiv-papers-ed5dcc0fdb3d" rel="external nofollow noopener" target="_blank">LLM Research Trends</a></li> </ul> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra/">Google Gemini updates: Flash 1.5, Gemma 2 and Project Astra</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/how-to-write-a-good-scientific-review/">How to write a good scientific review?</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/habits/">Habits</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work/">Regulate your blood sugar! — Nourish to Flourish: Harnessing Glycogen for Peak Performance at Work</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="//blog/2024/how-to-lead-when-you-are-not-in-charge/">How to lead when you are not in charge?</a> </li> <div id="giscus_thread" style="max-width: 930px; margin: 0 auto;"> <script>let giscusTheme=determineComputedTheme(),giscusAttributes={src:"https://giscus.app/client.js","data-repo":"lorenz-peter/lorenz-peter.github.io","data-repo-id":"","data-category":"Comments","data-category-id":"","data-mapping":"title","data-strict":"1","data-reactions-enabled":"1","data-emit-metadata":"0","data-input-position":"bottom","data-theme":giscusTheme,"data-lang":"en",crossorigin:"anonymous",async:""},giscusScript=document.createElement("script");Object.entries(giscusAttributes).forEach(([t,e])=>giscusScript.setAttribute(t,e)),document.getElementById("giscus_thread").appendChild(giscusScript);</script> <noscript>Please enable JavaScript to view the <a href="http://giscus.app/?ref_noscript" rel="external nofollow noopener" target="_blank">comments powered by giscus.</a> </noscript> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 Peter Lorenz. 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<nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="//"> <span class="font-weight-bold">Peter</span> Lorenz </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" 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-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.3">Jekyll</generator><link href="https://lorenz-peter.github.io/feed.xml" rel="self" type="application/atom+xml"/><link href="https://lorenz-peter.github.io/" rel="alternate" type="text/html" hreflang="en"/><updated>2024-11-12T01:08:03+00:00</updated><id>https://lorenz-peter.github.io/feed.xml</id><title type="html">blank</title><subtitle>Personal Website </subtitle><entry><title type="html">Confidence in public speaking and presenting</title><link href="https://lorenz-peter.github.io/blog/2024/confidence-in-public-speaking-and-presenting/" rel="alternate" type="text/html" title="Confidence in public speaking and presenting"/><published>2024-11-08T07:56:29+00:00</published><updated>2024-11-08T07:56:29+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/confidence-in-public-speaking-and-presenting</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/confidence-in-public-speaking-and-presenting/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">How to lead when you are not in charge?</title><link href="https://lorenz-peter.github.io/blog/2024/how-to-lead-when-you-are-not-in-charge/" rel="alternate" type="text/html" title="How to lead when you are not in charge?"/><published>2024-11-03T05:46:47+00:00</published><updated>2024-11-03T05:46:47+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/how-to-lead-when-you-are-not-in-charge</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/how-to-lead-when-you-are-not-in-charge/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">Parse the Paper List</title><link href="https://lorenz-peter.github.io/blog/2024/load-json/" rel="alternate" type="text/html" title="Parse the Paper List"/><published>2024-11-02T18:37:00+00:00</published><updated>2024-11-02T18:37:00+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/load-json</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/load-json/"><![CDATA[<div class="jupyter-notebook" style="position: relative; width: 100%; margin: 0 auto;"> <div class="jupyter-notebook-iframe-container"> <iframe src="/assets/jupyter/load_json.ipynb.html" style="position: absolute; top: 0; left: 0; border-style: none;" width="100%" height="100%" onload="this.parentElement.style.paddingBottom = (this.contentWindow.document.documentElement.scrollHeight + 10) + 'px'"></iframe> </div> </div>]]></content><author><name></name></author><category term="research"/><category term="research"/><summary type="html"><![CDATA[Parse the json file]]></summary></entry><entry><title type="html">Regulate your blood sugar! — Nourish to Flourish: Harnessing Glycogen for Peak Performance at Work</title><link href="https://lorenz-peter.github.io/blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work/" rel="alternate" type="text/html" title="Regulate your blood sugar! — Nourish to Flourish: Harnessing Glycogen for Peak Performance at Work"/><published>2024-10-19T10:28:22+00:00</published><updated>2024-10-19T10:28:22+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">Model Stealing (Related Work)</title><link href="https://lorenz-peter.github.io/blog/2024/rw-ms/" rel="alternate" type="text/html" title="Model Stealing (Related Work)"/><published>2024-10-17T18:37:00+00:00</published><updated>2024-10-17T18:37:00+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/rw-ms</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/rw-ms/"><![CDATA[<h2 id="a-complete-list-of-all-arxiv-model-stealing-papers-under-construction">A complete list of all (arXiv) model stealing papers (under construction)</h2> <p>by Peter Lorenz</p> <h3 id="description">Description</h3> <p>Staying current with the latest research in adversarial examples can be a daunting task, given the rapid increase in publications each year. I’ve dedicated myself to meticulously tracking these papers over the past few years and realized that sharing this curated list could benefit others.</p> <p>The sole criterion for selecting papers for this list is their primary focus on adversarial examples or extensive use of them. However, due to the sheer volume of papers, I can’t guarantee that I’ve captured every single one.</p> <p>Nevertheless, I’ve made every effort to include papers that predominantly discuss adversarial examples. Occasionally, there may be papers that do not strictly adhere to these criteria or where judgment calls were inconsistent. If you notice any discrepancies, please reach out via email, and I’ll promptly address them.</p> <p>As a result, this list remains unfiltered, encompassing any paper primarily centered around adversarial examples without passing judgment on their quality. For a curated selection of what I consider excellent and worthwhile reads, please refer to the Adversarial Machine Learning Reading List.</p> <p>A note on the data: This list updates automatically with new papers, sometimes before I can manually review them. I typically conduct this review twice a week to remove papers unrelated to adversarial examples. Therefore, there might be occasional false positives among the most recent entries. Each new, unverified entry includes a probability score from my simple yet well-calibrated bag-of-words classifier, indicating its likelihood of focusing on adversarial examples.</p> <p>Below, you’ll find the comprehensive paper list. I’ve also provided <a href="https://github.com/lorenz-peter/lorenz-peter.github.io/blob/master/assets/json/model_stealing_papers.json">JSON file</a> <a href="https://lorenz-peter.github.io/blog/2024/load-json/">guide</a> containing the same data, including one with abstracts. If you use this data for any interesting projects, I’d love to hear about your experiences.</p> <p>Recently, another website was deployed to discover research trends, <a href="https://researchtrend.ai/communities/AAML">researchtrend.ai</a>.</p> <p>In future, I might plan to to add also papers from <a href="https://eprint.iacr.org/">eprint.iacr.org</a>.</p> <h2 id="acknowledgment">Acknowledgment</h2> <p>The idea is derived from Nicolas Carlini: <a href="https://nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html">nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html</a>.</p> <h2 id="table">Table</h2> <table data-toggle="table" data-show-fullscreen="true" data-pagination="false" data-search="true" data-show-columns="true" data-url="/assets/json/model_stealing_papers.json"> <thead> <tr class="tr-class-1"> <th data-field="date" data-sortable="true" data-width="50">date</th> <th data-field="title" data-sortable="true" data-formatter="addLink">title</th> <th data-field="author" data-sortable="true">author(s)</th> <th data-field="link" data-visible="false">Link</th> </tr> </thead> </table> <script>function addLink(n,a){return`<a href="${a.link}" target="_blank">${n}</a>`}</script>]]></content><author><name></name></author><category term="research"/><category term="research"/><summary type="html"><![CDATA[shows latest related work]]></summary></entry><entry><title type="html">Analysis of Adversarial Examples (PhD Thesis)</title><link href="https://lorenz-peter.github.io/blog/2024/phdthesis/" rel="alternate" type="text/html" title="Analysis of Adversarial Examples (PhD Thesis)"/><published>2024-08-31T16:40:16+00:00</published><updated>2024-08-31T16:40:16+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/phdthesis</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/phdthesis/"><![CDATA[<h1 id="analysis-of-adversarial-examples">Analysis of Adversarial Examples</h1> <p>I earned my PhD with magna cum laude from Heidelberg University, Germany, where I was advised by my ex-team lead <a href="https://www.itwm.fraunhofer.de/en/departments/hpc/staff/janis-keuper.html">Janis Keuper</a> and supervised by Prof. <a href="https://hci.iwr.uni-heidelberg.de/vislearn/people/ullrich-koethe">Ullrich Köthe</a>. I am an external Ph.D. student at the University of Heidelberg (2nd best-ranked German university). My key research interest was the <strong>analysis of adversarial examples</strong> on DNN. In particular, deep neural networks’ <strong>robustness</strong> and <strong>trustworthiness</strong>.</p> <p>I also had the opportunity to intern with Prof. Sijia Liu (<a href="https://lsjxjtu.github.io/">MSU</a> &amp; <a href="https://mitibmwatsonailab.mit.edu/people/sijia-liu/">MIT-IBM</a>) and Pin-Yu Chen (<a href="https://sites.google.com/site/pinyuchenpage/home">MIT-IBM</a>), focusing on adversarial machine learning. Our “Visual Prompting for Adversarial Robustness” paper achieved recognition within the top 3% at the ICASSP conference.</p> <h2 id="thesis-abstract">Thesis Abstract</h2> <p>The rise of artificial intelligence (AI) has significantly impacted the field of computer vision (CV). In particular, deep learning (DL) has advanced the development of algorithms that comprehend visual data. In specific tasks, DL exhibits human capabilities and is impacting our everyday lives such as virtual assistants, entertainment or web searches. Despite of the success of visual algorithms, in this thesis we study the threat adversarial examples, which are input manipulation to let to misclassification.</p> <h2 id="important-links">Important Links</h2> <p><a href="https://www.mathinf.uni-heidelberg.de/en/thesis-defenses/analysis-of-adversarial-examples-2024-07-30">Defense announcement</a></p> <p><a href="https://drive.google.com/file/d/1tgZ5exAoadPo64Rd4rc7cAEjTGCuQi63/view?usp=sharing">Slides</a></p> <p><a href="https://archiv.ub.uni-heidelberg.de/volltextserver/35211/1/main.pdf">Thesis</a></p>]]></content><author><name></name></author><category term="thesis"/><category term="adversarial"/><category term="examples"/><summary type="html"><![CDATA[research]]></summary></entry><entry><title type="html">Habits</title><link href="https://lorenz-peter.github.io/blog/2024/habits/" rel="alternate" type="text/html" title="Habits"/><published>2024-06-06T16:21:53+00:00</published><updated>2024-06-06T16:21:53+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/habits</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/habits/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">How to write a good scientific review?</title><link href="https://lorenz-peter.github.io/blog/2024/how-to-write-a-good-scientific-review/" rel="alternate" type="text/html" title="How to write a good scientific review?"/><published>2024-06-06T16:05:07+00:00</published><updated>2024-06-06T16:05:07+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/how-to-write-a-good-scientific-review</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/how-to-write-a-good-scientific-review/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">Find the right conference venue!</title><link href="https://lorenz-peter.github.io/blog/2024/findvenue/" rel="alternate" type="text/html" title="Find the right conference venue!"/><published>2024-06-03T16:40:16+00:00</published><updated>2024-06-03T16:40:16+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/findvenue</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/findvenue/"><![CDATA[<h1 id="how-do-you-find-your-conference-in-trustworthy-ml">How do you find your conference in trustworthy ML?</h1> <p>If you have finished doing your experiments, it is about finding the right venue.</p> <h2 id="via-google-ranking">Via Google Ranking</h2> <ul> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_artificialintelligence">Artificial Intelligence</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computervisionpatternrecognition">Computer Vision</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computationallinguistics">Computational Linguistics</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computersecuritycryptography">Security and Privacy</a></li> </ul> <p>The h-index and median are both metrics used to evaluate the impact of scholarly research publications, particularly in the field of academia.</p> <ol> <li> <p><strong>h-index</strong>: The h-index is a numerical value that attempts to measure both the productivity and impact of the published work of a scientist or scholar. It’s calculated based on the number of papers the researcher has published and the number of citations each paper has received. The h-index is determined by arranging the researcher’s publications according to the number of citations they have received. The h-index is the highest number of publications that have at least the same number of citations. For example, if a researcher has an h-index of 20, it means they have published at least 20 papers, each of which has been cited at least 20 times.</p> </li> <li> <p><strong>Median</strong>: In the context of h-index, the median is typically used to represent the median number of citations received by the researcher’s publications. This value provides insight into the central tendency of the citation distribution of the researcher’s work. It helps to understand the typical level of impact or recognition the researcher’s papers have received. If a researcher’s median citation count is high, it suggests that their publications tend to receive a substantial number of citations, indicating a significant impact in their field.</p> </li> </ol> <p>Both the h-index and median are valuable tools for evaluating the impact and significance of a researcher’s contributions, although they each capture slightly different aspects of the citation profile.</p> <h2 id="other-rankings">Other Rankings</h2> <ul> <li><a href="https://www.iiti.ac.in/people/~artiwari/cseconflist.html">CORE</a></li> <li><a href="http://www.conferenceranks.com">conference ranks</a></li> </ul> <h2 id="deadlines-tracking">Deadlines Tracking</h2> <ul> <li><a href="https://aideadlin.es/?sub=ML,CV,NLP,DM,KR">AI</a></li> <li><a href="https://sec-deadlines.github.io">SEC</a></li> <li><a href="https://iacr.org/events/?order=submission">IACR</a></li> </ul> <h2 id="other-recommended-conferences-and-workshops-for-trustworthy-ml">Other Recommended Conferences and Workshops for Trustworthy ML</h2> <ul> <li><a href="https://aisec.cc">ACM AISec</a></li> <li><a href="https://satml.org">IEEE SaTML</a></li> <li><a href="https://facctconference.org">ACM FAccT</a></li> </ul> <h2 id="research-trends">Research Trends</h2> <ul> <li><a href="https://colab.research.google.com/drive/1u51Id90ML79UdZaKD23qglY0ZkEmmdwk?usp=sharing#scrollTo=metallic-aquatic">NeurIPS keywords</a></li> <li><a href="https://public.tableau.com/app/profile/joshpreston/viz/CVPR2024/CVPRtrends">CVPR Trends</a></li> <li><a href="https://researchtrends.ai">Researchtrends.ai</a></li> <li><a href="https://medium.com/gptalk/llm-research-trends-from-17k-arxiv-papers-ed5dcc0fdb3d">LLM Research Trends</a></li> </ul>]]></content><author><name></name></author><category term="writing"/><category term="icml,"/><category term="cvpr,"/><category term="conference"/><summary type="html"><![CDATA[conference]]></summary></entry><entry><title type="html">Google Gemini updates: Flash 1.5, Gemma 2 and Project Astra</title><link href="https://lorenz-peter.github.io/blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra/" rel="alternate" type="text/html" title="Google Gemini updates: Flash 1.5, Gemma 2 and Project Astra"/><published>2024-05-14T00:00:00+00:00</published><updated>2024-05-14T00:00:00+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[We’re sharing updates across our Gemini family of models and a glimpse of Project Astra, our vision for the future of AI assistants.]]></summary></entry></feed>
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+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.3">Jekyll</generator><link href="https://lorenz-peter.github.io/feed.xml" rel="self" type="application/atom+xml"/><link href="https://lorenz-peter.github.io/" rel="alternate" type="text/html" hreflang="en"/><updated>2024-11-13T02:29:47+00:00</updated><id>https://lorenz-peter.github.io/feed.xml</id><title type="html">blank</title><subtitle>Personal Website </subtitle><entry><title type="html">Confidence in public speaking and presenting</title><link href="https://lorenz-peter.github.io/blog/2024/confidence-in-public-speaking-and-presenting/" rel="alternate" type="text/html" title="Confidence in public speaking and presenting"/><published>2024-11-08T07:56:29+00:00</published><updated>2024-11-08T07:56:29+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/confidence-in-public-speaking-and-presenting</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/confidence-in-public-speaking-and-presenting/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">How to lead when you are not in charge?</title><link href="https://lorenz-peter.github.io/blog/2024/how-to-lead-when-you-are-not-in-charge/" rel="alternate" type="text/html" title="How to lead when you are not in charge?"/><published>2024-11-03T05:46:47+00:00</published><updated>2024-11-03T05:46:47+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/how-to-lead-when-you-are-not-in-charge</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/how-to-lead-when-you-are-not-in-charge/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">Parse the Paper List</title><link href="https://lorenz-peter.github.io/blog/2024/load-json/" rel="alternate" type="text/html" title="Parse the Paper List"/><published>2024-11-02T18:37:00+00:00</published><updated>2024-11-02T18:37:00+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/load-json</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/load-json/"><![CDATA[<div class="jupyter-notebook" style="position: relative; width: 100%; margin: 0 auto;"> <div class="jupyter-notebook-iframe-container"> <iframe src="/assets/jupyter/load_json.ipynb.html" style="position: absolute; top: 0; left: 0; border-style: none;" width="100%" height="100%" onload="this.parentElement.style.paddingBottom = (this.contentWindow.document.documentElement.scrollHeight + 10) + 'px'"></iframe> </div> </div>]]></content><author><name></name></author><category term="research"/><category term="research"/><summary type="html"><![CDATA[Parse the json file]]></summary></entry><entry><title type="html">Regulate your blood sugar! — Nourish to Flourish: Harnessing Glycogen for Peak Performance at Work</title><link href="https://lorenz-peter.github.io/blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work/" rel="alternate" type="text/html" title="Regulate your blood sugar! — Nourish to Flourish: Harnessing Glycogen for Peak Performance at Work"/><published>2024-10-19T10:28:22+00:00</published><updated>2024-10-19T10:28:22+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/regulate-your-blood-sugarnourish-to-flourish-harnessing-glycogen-for-peak-performance-at-work/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">Model Stealing (Related Work)</title><link href="https://lorenz-peter.github.io/blog/2024/rw-ms/" rel="alternate" type="text/html" title="Model Stealing (Related Work)"/><published>2024-10-17T18:37:00+00:00</published><updated>2024-10-17T18:37:00+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/rw-ms</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/rw-ms/"><![CDATA[<h2 id="a-complete-list-of-all-arxiv-model-stealing-papers-under-construction">A complete list of all (arXiv) model stealing papers (under construction)</h2> <p>by Peter Lorenz</p> <h3 id="description">Description</h3> <p>Staying current with the latest research in adversarial examples can be a daunting task, given the rapid increase in publications each year. I’ve dedicated myself to meticulously tracking these papers over the past few years and realized that sharing this curated list could benefit others.</p> <p>The sole criterion for selecting papers for this list is their primary focus on adversarial examples or extensive use of them. However, due to the sheer volume of papers, I can’t guarantee that I’ve captured every single one.</p> <p>Nevertheless, I’ve made every effort to include papers that predominantly discuss adversarial examples. Occasionally, there may be papers that do not strictly adhere to these criteria or where judgment calls were inconsistent. If you notice any discrepancies, please reach out via email, and I’ll promptly address them.</p> <p>As a result, this list remains unfiltered, encompassing any paper primarily centered around adversarial examples without passing judgment on their quality. For a curated selection of what I consider excellent and worthwhile reads, please refer to the Adversarial Machine Learning Reading List.</p> <p>A note on the data: This list updates automatically with new papers, sometimes before I can manually review them. I typically conduct this review twice a week to remove papers unrelated to adversarial examples. Therefore, there might be occasional false positives among the most recent entries. Each new, unverified entry includes a probability score from my simple yet well-calibrated bag-of-words classifier, indicating its likelihood of focusing on adversarial examples.</p> <p>Below, you’ll find the comprehensive paper list. I’ve also provided <a href="https://github.com/lorenz-peter/lorenz-peter.github.io/blob/master/assets/json/model_stealing_papers.json">JSON file</a> <a href="https://lorenz-peter.github.io/blog/2024/load-json/">guide</a> containing the same data, including one with abstracts. If you use this data for any interesting projects, I’d love to hear about your experiences.</p> <p>Recently, another website was deployed to discover research trends, <a href="https://researchtrend.ai/communities/AAML">researchtrend.ai</a>.</p> <p>In future, I might plan to to add also papers from <a href="https://eprint.iacr.org/">eprint.iacr.org</a>.</p> <h2 id="acknowledgment">Acknowledgment</h2> <p>The idea is derived from Nicolas Carlini: <a href="https://nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html">nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html</a>.</p> <h2 id="table">Table</h2> <table data-toggle="table" data-show-fullscreen="true" data-pagination="false" data-search="true" data-show-columns="true" data-url="/assets/json/model_stealing_papers.json"> <thead> <tr class="tr-class-1"> <th data-field="date" data-sortable="true" data-width="50">date</th> <th data-field="title" data-sortable="true" data-formatter="addLink">title</th> <th data-field="author" data-sortable="true">author(s)</th> <th data-field="link" data-visible="false">Link</th> </tr> </thead> </table> <script>function addLink(n,a){return`<a href="${a.link}" target="_blank">${n}</a>`}</script>]]></content><author><name></name></author><category term="research"/><category term="research"/><summary type="html"><![CDATA[shows latest related work]]></summary></entry><entry><title type="html">Analysis of Adversarial Examples (PhD Thesis)</title><link href="https://lorenz-peter.github.io/blog/2024/phdthesis/" rel="alternate" type="text/html" title="Analysis of Adversarial Examples (PhD Thesis)"/><published>2024-08-31T16:40:16+00:00</published><updated>2024-08-31T16:40:16+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/phdthesis</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/phdthesis/"><![CDATA[<h1 id="analysis-of-adversarial-examples">Analysis of Adversarial Examples</h1> <p>I earned my PhD with magna cum laude from Heidelberg University, Germany, where I was advised by my ex-team lead <a href="https://www.itwm.fraunhofer.de/en/departments/hpc/staff/janis-keuper.html">Janis Keuper</a> and supervised by Prof. <a href="https://hci.iwr.uni-heidelberg.de/vislearn/people/ullrich-koethe">Ullrich Köthe</a>. I am an external Ph.D. student at the University of Heidelberg (2nd best-ranked German university). My key research interest was the <strong>analysis of adversarial examples</strong> on DNN. In particular, deep neural networks’ <strong>robustness</strong> and <strong>trustworthiness</strong>.</p> <p>I also had the opportunity to intern with Prof. Sijia Liu (<a href="https://lsjxjtu.github.io/">MSU</a> &amp; <a href="https://mitibmwatsonailab.mit.edu/people/sijia-liu/">MIT-IBM</a>) and Pin-Yu Chen (<a href="https://sites.google.com/site/pinyuchenpage/home">MIT-IBM</a>), focusing on adversarial machine learning. Our “Visual Prompting for Adversarial Robustness” paper achieved recognition within the top 3% at the ICASSP conference.</p> <h2 id="thesis-abstract">Thesis Abstract</h2> <p>The rise of artificial intelligence (AI) has significantly impacted the field of computer vision (CV). In particular, deep learning (DL) has advanced the development of algorithms that comprehend visual data. In specific tasks, DL exhibits human capabilities and is impacting our everyday lives such as virtual assistants, entertainment or web searches. Despite of the success of visual algorithms, in this thesis we study the threat adversarial examples, which are input manipulation to let to misclassification.</p> <h2 id="important-links">Important Links</h2> <p><a href="https://www.mathinf.uni-heidelberg.de/en/thesis-defenses/analysis-of-adversarial-examples-2024-07-30">Defense announcement</a></p> <p><a href="https://drive.google.com/file/d/1tgZ5exAoadPo64Rd4rc7cAEjTGCuQi63/view?usp=sharing">Slides</a></p> <p><a href="https://archiv.ub.uni-heidelberg.de/volltextserver/35211/1/main.pdf">Thesis</a></p>]]></content><author><name></name></author><category term="thesis"/><category term="adversarial"/><category term="examples"/><summary type="html"><![CDATA[research]]></summary></entry><entry><title type="html">Habits</title><link href="https://lorenz-peter.github.io/blog/2024/habits/" rel="alternate" type="text/html" title="Habits"/><published>2024-06-06T16:21:53+00:00</published><updated>2024-06-06T16:21:53+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/habits</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/habits/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">How to write a good scientific review?</title><link href="https://lorenz-peter.github.io/blog/2024/how-to-write-a-good-scientific-review/" rel="alternate" type="text/html" title="How to write a good scientific review?"/><published>2024-06-06T16:05:07+00:00</published><updated>2024-06-06T16:05:07+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/how-to-write-a-good-scientific-review</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/how-to-write-a-good-scientific-review/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">Find the right conference venue!</title><link href="https://lorenz-peter.github.io/blog/2024/findvenue/" rel="alternate" type="text/html" title="Find the right conference venue!"/><published>2024-06-03T16:40:16+00:00</published><updated>2024-06-03T16:40:16+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/findvenue</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/findvenue/"><![CDATA[<h1 id="how-do-you-find-your-conference-in-trustworthy-ml">How do you find your conference in trustworthy ML?</h1> <p>If you have finished doing your experiments, it is about finding the right venue.</p> <h2 id="via-google-ranking">Via Google Ranking</h2> <ul> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_artificialintelligence">Artificial Intelligence</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computervisionpatternrecognition">Computer Vision</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computationallinguistics">Computational Linguistics</a></li> <li><a href="https://scholar.google.de/citations?view_op=top_venues&amp;hl=en&amp;vq=eng_computersecuritycryptography">Security and Privacy</a></li> </ul> <p>The h-index and median are both metrics used to evaluate the impact of scholarly research publications, particularly in the field of academia.</p> <ol> <li> <p><strong>h-index</strong>: The h-index is a numerical value that attempts to measure both the productivity and impact of the published work of a scientist or scholar. It’s calculated based on the number of papers the researcher has published and the number of citations each paper has received. The h-index is determined by arranging the researcher’s publications according to the number of citations they have received. The h-index is the highest number of publications that have at least the same number of citations. For example, if a researcher has an h-index of 20, it means they have published at least 20 papers, each of which has been cited at least 20 times.</p> </li> <li> <p><strong>Median</strong>: In the context of h-index, the median is typically used to represent the median number of citations received by the researcher’s publications. This value provides insight into the central tendency of the citation distribution of the researcher’s work. It helps to understand the typical level of impact or recognition the researcher’s papers have received. If a researcher’s median citation count is high, it suggests that their publications tend to receive a substantial number of citations, indicating a significant impact in their field.</p> </li> </ol> <p>Both the h-index and median are valuable tools for evaluating the impact and significance of a researcher’s contributions, although they each capture slightly different aspects of the citation profile.</p> <h2 id="other-rankings">Other Rankings</h2> <ul> <li><a href="https://www.iiti.ac.in/people/~artiwari/cseconflist.html">CORE</a></li> <li><a href="http://www.conferenceranks.com">conference ranks</a></li> <li><a href="https://people.engr.tamu.edu/guofei/sec_conf_stat.htm">sec conf ranks</a></li> </ul> <h2 id="journals">Journals</h2> <p>One key difference between journal and conference publications is the review process. Journals typically involve a more thorough and time-consuming review process, with reviewers having more time to provide detailed feedback. As a result, the publication timeline for journals is often longer than for conferences.</p> <ul> <li><a href="https://en.wikipedia.org/wiki/IEEE_Transactions_on_Pattern_Analysis_and_Machine_Intelligence">TPAMI</a></li> </ul> <h2 id="deadlines-tracking">Deadlines Tracking</h2> <ul> <li><a href="https://aideadlin.es/?sub=ML,CV,NLP,DM,KR">AI</a></li> <li><a href="https://sec-deadlines.github.io">SEC</a></li> <li><a href="https://iacr.org/events/?order=submission">IACR</a></li> </ul> <h2 id="other-recommended-conferences-and-workshops-for-trustworthy-ml">Other Recommended Conferences and Workshops for Trustworthy ML</h2> <ul> <li><a href="https://aisec.cc">ACM AISec</a></li> <li><a href="https://satml.org">IEEE SaTML</a></li> <li><a href="https://facctconference.org">ACM FAccT</a></li> </ul> <h2 id="research-trends">Research Trends</h2> <ul> <li><a href="https://colab.research.google.com/drive/1u51Id90ML79UdZaKD23qglY0ZkEmmdwk?usp=sharing#scrollTo=metallic-aquatic">NeurIPS keywords</a></li> <li><a href="https://public.tableau.com/app/profile/joshpreston/viz/CVPR2024/CVPRtrends">CVPR Trends</a></li> <li><a href="https://researchtrends.ai">Researchtrends.ai</a></li> <li><a href="https://medium.com/gptalk/llm-research-trends-from-17k-arxiv-papers-ed5dcc0fdb3d">LLM Research Trends</a></li> </ul>]]></content><author><name></name></author><category term="writing"/><category term="icml,"/><category term="cvpr,"/><category term="conference"/><summary type="html"><![CDATA[conference]]></summary></entry><entry><title type="html">Google Gemini updates: Flash 1.5, Gemma 2 and Project Astra</title><link href="https://lorenz-peter.github.io/blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra/" rel="alternate" type="text/html" title="Google Gemini updates: Flash 1.5, Gemma 2 and Project Astra"/><published>2024-05-14T00:00:00+00:00</published><updated>2024-05-14T00:00:00+00:00</updated><id>https://lorenz-peter.github.io/blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra</id><content type="html" xml:base="https://lorenz-peter.github.io/blog/2024/google-gemini-updates-flash-15-gemma-2-and-project-astra/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[We’re sharing updates across our Gemini family of models and a glimpse of Project Astra, our vision for the future of AI assistants.]]></summary></entry></feed>
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