AutoML Seminar
@AutomlSeminar
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Talks on topics related to #automl. Part of the @ELLISforEurope Units Berlin and Freiburg. Past talks: https://t.co/viEMm3CweJ
Joined March 2022
🧠 Next talk Oct 30 · 3:00 PM CET — @JakeMRobertson & @Arik_Reuter: Do-PFN: In-Context Learning for Causal Effect Estimation. Explore PFNs for causal estimation from observational tabular data. 🔗
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🎥 New #AutoMLSeminar talk by Jan van Rijn is online! Multi-Objective #AutoML: Towards Accurate and Robust Models Watch now 👉
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Join for our next talk by Jan van Rijn (Thursday 3:00 PM CET on " Multi-Objective AutoML: Towards Accurate and Robust Models." 🔗
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Carolin's #AutoML Seminar talk on 'carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks' is now online! 🎥 Watch here 👉 https://t.co/2ujTNMUvRl
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Don’t miss this the next #AutoML Seminar talk on Oct 2 3:00 PM CET! Carolin Benjamins will talk about: "carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks". More details:
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This week at the #AutoML Seminar: @AcerbiLuigi presents “Accelerating Bayesian Inference and Data Acquisition via Amortization” 📅 Sept 25, 3:00 PM CET ➡️ Free, open to all: 40 mins talk + 20 mins discussion Details:
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🎉 New AutoML Seminar Talk Online! Check out the excellent presentation by @ElenaRaponi_ and Niki van Stein, now available on our YT channel! They introduce a fascinating new approach to automatically designing better Bayesian Optimization algorithms.
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This week, @ElenaRaponi_ and Niki van Stein will present how you can leverage large language models (LLMs) to automatically generate Bayesian optimization algorithms.
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This week @LennartPurucker will present "TabArena: a living benchmark for tabular data"! More details:
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Tomorrow (Thursday) at 3pm @_geoalgo_ will talk about using AutoML to tune LLM judges for 1/1000 of the costs. See
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New talk by Lennart on automated prompt engineering is now online: https://t.co/tqlIyPSCLm. This seems to be highly promising direction for AutoML in the context of #LLMs
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This Thursday 3pm CET, Lennart Schneider will present his ICML paper on optimizing few-shot prompts for large language models using multi-fidelity hyperparameter optimization. More details:
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How does Bayesian optimization work in high dimensions? Check out Leonard Papenmeier's talk at the AutoML Seminar:
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This week (Thursday 1pm CEST), we have Leonard Papenmeier talking about how Bayesian optimization works in high-dimensional spaces:
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Fantastic talk by @innixma on the role of foundation models in AutoML is now online:
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Don't miss this week's talk (Thursday, 5:30 CET) by @innixma from the @autogluon team on "AutoML in the Age of Structured Foundation Models".
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New talk by @jonasgeiping is now online on how to scale test-time compute via latent reasoning:
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This week (Thursday at 4 PM), @jonasgeiping will be giving a talk on his latest work, "Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach." More details:
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New talk by Thomas Nagler and Lennart Schneider is now online on how to improve generalization of hyperparameter optimization:
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This week we have Thomas Nagler and Lennart Schneider talking about their recent paper on "Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization" at the AutoML Seminar:
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