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[AUTOML23] SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Prompt engineering and serverless inference: closing the open model gap
Bayesian Optimization Meets Self-Distillation
High-Dimensional Black-Box Optimisation in Small Data Regimes | Haitham Bou Ammar
Bayesian Optimization (Framework) Intended for Real Experiments
Consistent high-dimensional Bayesian variable selection via penalized credible regions
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Last Updated: September 28, 2026
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Authors: Yihang Shen, Carl Kingsford 2023.automl.cc/program/accepted_papers/ Authors: Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim ... We combine adjoint solvers with gradient-augmented Download 1M+ code from codegive.com/9e915e1 tutorial on vanilla See how prompt engineering helps an open-source model get close to a frontier model's accuracy on CoreWeave Serverless ... ICARL Seminar Series - 2022 Spring by Johannes P. Dürholt at the AutoML Summer School 2026. Speaker: Howard Bondell The Third Biannual Duke Workshop on Sensing and Analysis of
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