AutoML 2025 Methods Track Submissions

PiML: Automated Machine Learning Workflow Optimization using LLM Agents
Abhishek Chopde, Fardeen Pettiwala, Sankar Kirubananth, Sai Kiran Botla, Pachipulusu Ayyappa Kethan
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Feasibility-Driven Trust Region Bayesian Optimization
Paolo Ascia, Elena Raponi, Thomas Bäck, Duddeck
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Iterative Monte Carlo Tree Search for Neural Architecture Search
Mehraveh Javan Roshtkhari, Matthew Toews, Marco Pedersoli
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Frozen Layers: Memory-efficient Many-fidelity Hyperparameter Optimization
Neeratyoy Mallik, Timur Carstensen, Frank Hutter, Martin Rapp
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Fast Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Peter I. Frazier
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
FlowGen: Bayesian Search for Pareto-Optimal Generative AI
Alexander Conway, Debadeepta Dey, Stefan Hackmann, Matthew Hausknecht, Michael Douglas Schmidt, Mark Lewis Steadman, Nick Volynets
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Learning-to-Rank for AutoML: A Simple and Robust Alternative to Score-Based Pipeline Selection
Hernan Ceferino Vazquez, Jorge Sánchez, Verónica Bogado, Pucci Romero Tobias
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Regularized Neural Ensemblers
Sebastian Pineda Arango, Maciej Janowski, Lennart Purucker, Arber Zela, Frank Hutter, Josif Grabocka
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
What Makes Freezing Layers in Deep Neural Networks Effective? A Linear Separability Perspective
Collin Coil, Nick Cheney
- Published: 03 Jun 2025, Last Modified: 04 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
EG-ENAS: Efficient and Generalizable Evolutionary Neural Architecture Search for Image Classification
Mateo Avila Pava, Andreas M Kist, René Groh
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Hyperparameter Optimization via Interacting with Probabilistic Circuits
Jonas Seng, Fabrizio Ventola, Zhongjie Yu, Kristian Kersting
- Published: 03 Jun 2025, Last Modified: 04 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
SmartCal: A Novel Automated Approach to Classifier Probability Calibration
Mohamed Maher Abdelrahman, Osama Fayez Oun, Youssef Medhat, Mariam Magdy Elseedawy, Yara Mostafa Marei, Abdullah Ibrahim, Radwa Mohamed El Shawi
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
AutoPDL: Automatic Prompt Optimization for LLM Agents
Claudio Spiess, Mandana Vaziri, Louis Mandel, Martin Hirzel
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation
Sigrid Passano Hellan, Huibin Shen, Francois-Xavier Aubet, David Salinas, Aaron Klein
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Multi-layer Stack Ensembles for Time Series Forecasting
Nathanael Bosch, Oleksandr Shchur, Nick Erickson, Michael Bohlke-Schneider, Ali Caner Turkmen
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Transferrable Surrogates in Expressive Neural Architecture Search Spaces
Shiwen Qin, Gabriela Kadlecová, Martin Pilát, Shay B Cohen, Roman Neruda, Elliot J. Crowley, Jovita Lukasik, Linus Ericsson
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Overtuning in Hyperparameter Optimization
Lennart Schneider, Bernd Bischl, Matthias Feurer
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
CAPO: Cost-Aware Prompt Optimization
Tom Zehle, Moritz Schlager, Timo Heiß, Matthias Feurer
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone
Revisiting Learning Rate Control
Micha Henheik, Theresa Eimer, Marius Lindauer
- Published: 03 Jun 2025, Last Modified: 03 Jun 2025
- AutoML 2025 Methods Track
- Readers: Everyone