iiinova — where your digital self keeps evolving

CSML IIT Lab @pontilgroup.bsky.social · 25/08/2026

Representations for the Physical Sciences Workshop @ NeurIPS 2026🇫🇷 We’re bringing together researchers working on AI for science, representation learning, and physical systems, with a particular focus on self-supervision, transfer learning, adaptive sampling, and tokenization.

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CSML IIT Lab @pontilgroup.bsky.social · 08/07/2026

ICML 2026 is underway in Seoul, and I'm delighted that our group has four papers on the program this week: 📍 Tuesday, July 7 · Hall A · Poster #4413 Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression icml.cc/virtual/2026...

icml.cc

ICML Poster Outcome-Aware Spectral Feature Learning for Instrumental Variable RegressionICML 2026

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CSML IIT Lab @pontilgroup.bsky.social · 17/12/2025

Almost 5 years in the making... "Hyperparameter Optimization in Machine Learning" is finally out! 📘 We designed this monograph to be self-contained, covering: Grid, Random & Quasi-random search, Bayesian & Multi-fidelity optimization, Gradient-based methods, Meta-learning. arxiv.org/abs/2410.22854

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CSML IIT Lab @pontilgroup.bsky.social · 28/11/2025

🚨 OpenReview might have leaked names, but it won't leak the best hyperparameters, unfortunately! 😅 Tired of the drama? Solve your HPO problems before the ICML deadline with this new monograph by our own Luca Franceschi & Massimiliano Pontil (& colleagues). arxiv.org/abs/2410.22854

arxiv.org

Hyperparameter Optimization in Machine Learning

Hyperparameters are configuration variables controlling the behavior of machine learning algorithms. They are ubiquitous in machine learning and artificial intelligence and the choice of their values ...

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CSML IIT Lab @pontilgroup.bsky.social · 14/11/2025

📢 Upcoming Talk at Our Lab We’re excited to host Arthur Bizzi from EPFL for a research talk next week! Title: Towards Neural Kolmogorov Equations: Parallelizable SDE Learning with Neural PDEs 🗓 Date: November 19 ⏰ Time: 16:00 CET 📍 Galileo Sala, CHT @iitalk.bsky.social

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CSML IIT Lab @pontilgroup.bsky.social · 02/05/2025

Excited to share our group’s latest work at #AISTATS2025! 🎓 Tackling concentration in dependent data settings with empirical Bernstein bounds for Hilbert space-valued processes. 📍Catch the poster tomorrow! 🔁 See the original tweet for details!

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CSML IIT Lab @pontilgroup.bsky.social · 09/04/2025

DeltaProduct is here! Achieve better state tracing through highly parallel execution. Explore more!🚀

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CSML IIT Lab @pontilgroup.bsky.social · 15/01/2025

1/ 🚀 Over the past two years, our team, CSML, at IIT, has made significant strides in the data-driven modeling of dynamical systems. Curious about how we use advanced operator-based techniques to tackle real-world challenges? Let’s dive in! 🧵👇

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CSML IIT Lab @pontilgroup.bsky.social · 15/01/2025

An inspiring dive into understanding dynamical processes through 'The Operator Way.' A fascinating approach made accessible for everyone—check it out! 👇👀

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Reposted by CSML IIT Lab

Riccardo Grazzi @riccardograzzi.bsky.social · 10/12/2024

Excited to present "Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues" at the M3L workshop at #NeurIPS buff.ly/3BlcD4y If interested, you can attend the presentation the 14th at 15:00, pass at the afternoon poster session, or DM me to discuss :)

buff.ly

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

Linear Recurrent Neural Networks (LRNNs) such as Mamba, RWKV, GLA, mLSTM, and DeltaNet have emerged as efficient alternatives to Transformers in large language modeling, offering linear scaling with…

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Reposted by CSML IIT Lab

Pietro Novelli @pienovelli.bsky.social · 12/12/2024

In his book “The Nature of Statistical Learning” V. Vapnik wrote: “When solving a given problem, try to avoid a more general problem as an intermediate step”

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CSML IIT Lab @pontilgroup.bsky.social · 10/12/2024

At #NeurIPS2024 🇨🇦 our group will present 7 contributions! These span a diverse array of topics: from theoretical advances in stochastic processes and reinforcement learning to applications in molecular dynamics and uncertainty quantification.

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Reposted by CSML IIT Lab

Marco Pratticò @marcopra.bsky.social · 26/11/2024

🎉 I am happy to share that I co-authored my first paper, “Operator World Models for Reinforcement Learning,” published at #NeurIPS2024! 🚀 Glad to present it in Vancouver 🇨🇦. See you there! #AI #ReinforcementLearning @pontilgroup.bsky.social arxiv.org/pdf/2406.19861

arxiv.org

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