Alberto Maria Metelli
@alberto_metelli
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Assistant Professor @polimi. Co-founder of ML Cube. Reinforcement Learning.
Milan, Italy
Joined November 2021
🚀 Congratulations to @marcomussi95 for winning the prestigious Dimitris N. Chorafas Prize for his PhD thesis “Online Learning Methods for Pricing and Advertising.” A remarkable achievement! 🎉
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At #EWRL2025 in Tübingen, @alberto_metelli and @papinimat presented their contributed talks - great insights on inverse RL and policy gradients shared with the community!
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We've extended the deadline for our workshop's calls for papers/ideas! Submit your work by August 29 AoE. Instructions on the website:
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The OpenReview link for our calls (for papers and ideas) is available, submit here: https://t.co/eqkSQFicmx We look forward to receiving your submissions!
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The @rl3polimi group will be at #ICML2025 with 6 papers, including 1 position paper! 🎉 We’ll be sharing details about each contribution in the coming days—stay tuned! Looking forward to connecting in Vancouver 🇨🇦
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✨ Excited to be at COLT 2025 in Lyon this week with @gianmarcogena! We’ll be presenting an Open Problem on heavy-tailed bandits this Friday. Happy to chat if you're around!
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Four projects of @polimi have been awarded funding under the Fondo Italiano per la Scienza, the fund for basic research set up by @mur_gov_. Congratulations to Giorgio Besagni, @fiorito_daniele, @MxgTeo and @alberto_metelli! For more information: https://t.co/TUhujsy0ov
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From research to run day - RL3 showed up at #POLIMIRUN 2025! 🏃 Missing in the photo: our top runners @PaoloBonetti15 and @alessio_russo97 💎 #RL3 #Polimi #Running
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🚨 We're hiring! We are looking for postdocs and PhD students to join the Reinforcement Learning group at @polimi in Fall 2025 to work on the theory and practice of human feedback in RL. 📅 Apply by May 31, 2025 🔗 https://t.co/32VwgR13gU 🔁 Spread the word!
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Meet the recipients of the 2024 ACM A.M. Turing Award, Andrew G. Barto and Richard S. Sutton! They are recognized for developing the conceptual and algorithmic foundations of reinforcement learning. Please join us in congratulating the two recipients! https://t.co/GrDfgzW1fL
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🌟 Our PhD student @montenegronwski has been featured on the Root Access Podcast! Alessandro dives into his paper, Learning Optimal Deterministic Policies with Stochastic Policy Gradients ( https://t.co/SOZnPhzeIF). 🎧 Full episode here: https://t.co/1z2YForqQn
#RL#RootAccess
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Hey everyone! At NeurIPS 2024 this week me, @mirco_mutti and @alberto_metelli have presented our novel paper on the sample complexity of inverse RL in linear MDPs. Check it out! https://t.co/sRqFKMdDaf
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✨ Powerful Constrained Convergence! ✨ The new work from @rl3polimi was presented at @NeurIPSConf! What is it? Last-iterate convergence of Policy Gradients for Continuous Constrained RL. If you missed our (painful) paper, here it is: https://t.co/7BmRXpTiYW See you! 👋🏻
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Excited to announce that RL3 has 6 papers accepted at NeurIPS 2024! 🎉 Stay tuned for more details on each paper in the coming weeks. We look forward to sharing our work with the community! #NeurIPS #RL3 #ReinforcementLearning #AI #Research
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🚀 Exciting News! 🚀 @protoss1986 and I are thrilled to announce our new exercise book, The Machine Learning Gym! The perfect resource for mastering Machine Learning with hands-on exercises and Python code. 📖 Learn more:
lnkd.in
This link will take you to a page that’s not on LinkedIn
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💣 For those of you attending @RL_Conference these days, make sure to pass by the poster by @gianlucadrappo this afternoon if you want to get to know better some new theoretical guarantees in hierarchical RL algorithms!
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Had a blast at the #ICML2024 workshops @arlet_workshop and FoRLaC! It was really cool to see everyone’s enthusiasm and organizing ARLET was a lot of fun. Thanks to everyone involved for making it such an enjoyable experience, see you at the next edition! 🫡
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🚀And here is the incredible RL3 team that attended #ICML2024! Keep an eye out for our upcoming research updates! #RL3 #ReinforcementLearning #Research
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The accepted papers are now public on OpenReview: https://t.co/sa22iPVWQw Come and join us today to chat with the authors!
openreview.net
Welcome to the OpenReview homepage for ICML 2024 Workshop ARLET
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📣 How can we learn sequential decision problems where actions impact specific system parts with intermediate effects? In our #ICML2024 paper, we introduce factored reward bandits and provide regret lower bounds and tight algorithms. 🗓️ Wed, Jul 24, 13:30 -- Poster Session 4
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