Machine Learning Lab

912 posts

Machine Learning Lab

Machine Learning Lab

@MaleLabTs

Machine Learning Lab is directed by prof @sbarbonjr, hosted at @DiaUnits, @UniTrieste, and hosts PostDocs, PhD students and MS students.

Trieste, Italy Sumali Ocak 2012
62 Sinusundan17.1K Mga Tagasunod
Machine Learning Lab nag-retweet
Sylvio Barbon Junior
Sylvio Barbon Junior@sbarbonjr·
RF importance tells us the main ingredients; DPGExplainer (via LRC) tells us the recipe. In this new post (DPGExplainer Saga — Episode 2: Wine), I compare RF importance with DPG predicate influence (LRC) on the classic Wine dataset. Here: lnkd.in/dxDizDHC @MaleLabTs
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Machine Learning Lab nag-retweet
Sylvio Barbon Junior
Sylvio Barbon Junior@sbarbonjr·
Gostaria de compartilhar com vocês o meu novo livro!!! Inteligência Artificial em Ciência Animal: Aplicações em Pesquisa e na Indústria! @MaleLabTs
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Andrew Ng
Andrew Ng@AndrewYNg·
NeurIPS received 21,575 paper submissions this year. Our Agentic Reviewer, released last week, just surpassed this in number of papers submitted and reviewed. It's clear agentic paper reviewing is here to stay and will be impactful!
Andrew Ng@AndrewYNg

Releasing a new "Agentic Reviewer" for research papers. I started coding this as a weekend project, and @jyx_su made it much better. I was inspired by a student who had a paper rejected 6 times over 3 years. Their feedback loop -- waiting ~6 months for feedback each time -- was painfully slow. We wanted to see if an agentic workflow can help researchers iterate faster. When we trained the system on ICLR 2025 reviews and measured Spearman correlation (higher is better) on the test set: - Correlation between two human reviewers: 0.41 - Correlation between AI and a human reviewer: 0.42 This suggests agentic reviewing is approaching human-level performance. The agent grounds its feedback by searching arXiv, so it works best in fields like AI where research is freely published there. It’s an experimental tool, but I hope it helps you with your research. Check it out here: paperreview.ai

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Sylvio Barbon Junior
Sylvio Barbon Junior@sbarbonjr·
Call for Papers – 4th World Conference on Explainable Artificial Intelligence (XAI 2026) Be part of the global conversation shaping the future of transparent and trustworthy AI! Submission: lnkd.in/dn469BxU Deadline: February 1, 2026 @MaleLabTs
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Sylvio Barbon Junior
Sylvio Barbon Junior@sbarbonjr·
O futuro da Inteligência Artificial é explicável. E você, vai ficar de fora? youtube.com/watch?v=aO3Qh_… Vem com a gente para a 4th World Conference on Explainable Artificial Intelligence (xAI 2026), no Brasil!!! @MaleLabTs
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Bogdan Filipič
Bogdan Filipič@BogdanFilipic·
The 2025 @EvostarConf in Trieste summarized: well-prepared conference, constructive atmosphere and hospitable hosts. Thanks to both participants and organizers.
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Machine Learning Lab nag-retweet
Sylvio Barbon Junior
Sylvio Barbon Junior@sbarbonjr·
I'd like to invite everyone attending #IJCNN25 to check out the presentation of #TPOT-Clustering! Matheus Camilo da Silva (@MaleLabTs) will be presenting this new tool, developed as part of his PhD project. Yes, you can use AutoML for clustering!
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Sylvio Barbon Junior
Sylvio Barbon Junior@sbarbonjr·
AI is making food safer—spotting contamination, checking freshness & more. But can we really trust these "black box" models? Our new survey shows how #XAI can open up AI in Food Engineering, making decisions clearer for everyone! arxiv.org/pdf/2504.10527 @MaleLabTs
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Mathieu
Mathieu@miniapeur·
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Per Kristian Lehre
Per Kristian Lehre@pklehre·
Fully funded PhD scholarship available on Theory of Evolutionary Algorithms within my research group. We do work at the intersection of evolutionary computation, theoretical computer science and AI. Please get in touch with me for further details. linkedin.com/hiring/jobs/40…
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MIB-Lab@Queen's
MIB-Lab@Queen's@MIB_at_Queens·
Excited to share our new survey on evolutionary computation (EC) and explainable AI (XAI)! Many thanks to our amazing co-authors. We hope this article serves as a valuable resource for the research community. ieeexplore.ieee.org/document/10730…
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