AutoML 2024 Workshop Track Submissions

Automated Prior Elicitation from Large Language Models for Bayesian Logistic Regression
Henry Gouk, Boyan Gao
- Published: 12 Jul 2024, Last Modified: 12 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
In-Context Learning for Latency Estimation
Timur Carstensen, Thomas Elsken, Martin Rapp
- Published: 12 Jul 2024, Last Modified: 21 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Fine-Tuning LLMs for Automated Feature Engineering
Yoichi Hirose, Kento Uchida, Shinichi Shirakawa
- Published: 12 Jul 2024, Last Modified: 16 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
LoRA-DARTS: Low Rank Adaptation for Differentiable Architecture Search
Arjun Krishnakumar, Abhash Kumar Jha, Shakiba Moradian, Martin Rapp, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik, Samir Garibov, Edward Bergman, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks
Tom Julian Viering, Steven Adriaensen, Herilalaina Rakotoarison, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Cost-Efficient Training for Automated Algorithm Selection
Erdem Kuş, Nguyen Dang, Ozgur Akgun, Ian Miguel
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Towards Efficient Search for Customized Activation Functions With Gradient Descent
Lukas Strack, Mahmoud Safari, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 12 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
LMEMs for post-hoc analysis of HPO Benchmarking
Anton Merlin Geburek, Neeratyoy Mallik, Danny Stoll, Xavier Bouthillier, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Beyond Graph-Based Modeling for Hierarchical Neural Architecture Search
Lum Birinxhiku, Danny Stoll, Simon Schrodi, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
einspace: Searching for Neural Architectures from Fundamental Operations
Linus Ericsson, Miguel Espinosa, Chenhongyi Yang, Antreas Antoniou, Amos Storkey, Shay B Cohen, Steven McDonagh, Elliot J. Crowley
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Rethinking of Encoder-based Warm-start Methods in Hyperparameter Optimization
Dawid Płudowski, Antoni Zajko, Katarzyna Woźnica, Anna Kozak
- Published: 12 Jul 2024, Last Modified: 12 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Fast Optimizer Benchmark
Simon Blauth, Tobias Bürger, Zacharias Häringer, Jörg K.H. Franke, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
FairPFN: Transformers Can Do Counterfactual Fairness
Jake Robertson, Noah Hollmann, Noor Awad, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Graph is All You Need? Lightweight Data-agnostic Neural Architecture Search without Training
Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Chunheng Jiang, Jianxi Gao
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC
Philipp Bordne, M Asif Hasan, Edward Bergman, Noor Awad, André Biedenkapp
- Published: 12 Jul 2024, Last Modified: 13 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Do Tree-based Models Need Data Preprocessing?
Hubert Ruczyński, Anna Kozak
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models
Ivo Rapant, Lennart Purucker, Fabio Ferreira, Sebastian Pineda Arango, Arlind Kadra, Josif Grabocka, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost
Jannis Maier, Felix Möller, Lennart Purucker
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
NOSBench-101: Towards Reproducible Neural Optimizer Search
Goktug Karakasli, Steven Adriaensen, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Beyond the Threshold: Time Is All You Need
Stefan Dendorfer, Andreas M Kist
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
FEATHERS: Federated Architecture and Hyperparameter Search
Jonas Seng, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
- Published: 12 Jul 2024, Last Modified: 09 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces
Aryan Deshwal, Sait Cakmak, Yuhou Xia, David Eriksson
- Published: 12 Jul 2024, Last Modified: 13 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation
Dong Bok Lee, Aoxuan Silvia Zhang, Byungjoo Kim, Junhyeon Park, Juho Lee, Sung Ju Hwang, Hae Beom Lee
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter
- Published: 12 Jul 2024, Last Modified: 14 Aug 2024
- AutoML 2024 Workshop
- Readers: Everyone