OpenML Benchmarking Suites

11 August 2017

Jan N. van Rijn

Papers citing "OpenML Benchmarking Suites"

35 / 35 papers shown

Title
Tabular Embeddings for Tables with Bi-Dimensional Hierarchical Metadata and Nesting Gyanendra Shrestha Chutain Jiang Sai Akula Vivek Yannam Anna Pyayt Michael Gubanov LMTD 97 0 0 20 Feb 2025
EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Networks Michael Arbel David Salinas Frank Hutter 73 2 0 10 Feb 2025
Dynamic Post-Hoc Neural Ensemblers Sebastian Pineda Arango Maciej Janowski Lennart Purucker Arber Zela Frank Hutter Josif Grabocka UQCV 36 0 0 06 Oct 2024
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 46 3 0 26 Jun 2024
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data Valentin Margraf Marcel Wever Sandra Gilhuber Gabriel Marques Tavares Thomas Seidl Eyke Hüllermeier 44 0 0 25 Jun 2024
AnnotatedTables: A Large Tabular Dataset with Language Model Annotations Yaojie Hu Ilias Fountalis Jin Tian N. Vasiloglou LMTD 36 3 0 24 Jun 2024
HyperFast: Instant Classification for Tabular Data David Bonet D. M. Montserrat Xavier Giró-i-Nieto A. Ioannidis 46 15 0 22 Feb 2024
Had enough of experts? Quantitative knowledge retrieval from large language models David Selby Kai Spriestersbach Yuichiro Iwashita Dennis Bappert Archana Warrier Sumantrak Mukherjee Muhammad Nabeel Asim Koichi Kise Sebastian Vollmer 44 0 0 12 Feb 2024
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data Wei-Yao Wang Wei-Wei Du Derek Xu Wei Wang Wenjie Peng LMTD 38 7 0 02 Feb 2024
Prevalidated ridge regression is a highly-efficient drop-in replacement for logistic regression for high-dimensional data Angus Dempster Geoffrey I. Webb Daniel F. Schmidt 29 0 0 28 Jan 2024
MotherNet: Fast Training and Inference via Hyper-Network Transformers Andreas Müller Carlo Curino Raghu Ramakrishnan LMTD 43 2 0 14 Dec 2023
CAST: Cluster-Aware Self-Training for Tabular Data Minwook Kim Juseong Kim Kibeom Kim Giltae Song 33 0 0 10 Oct 2023
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models Lennart Schneider B. Bischl Janek Thomas 30 6 0 17 Jul 2023
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables Jaehyun Nam Jihoon Tack Kyungmin Lee Hankook Lee Jinwoo Shin LMTD SSL 18 31 0 02 Mar 2023
Towards Personalized Preprocessing Pipeline Search Diego Martinez Daochen Zha Qiaoyu Tan Xia Hu AI4TS 29 2 0 28 Feb 2023
Conceptual Views on Tree Ensemble Classifiers Tom Hanika Johannes Hirth 37 4 0 10 Feb 2023
Task Selection for AutoML System Evaluation Jon Lorraine Nihesh Anderson Chansoo Lee Quentin de Laroussilhe Mehadi Hassen 46 4 0 26 Aug 2022
A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data sets Jacques Wainer 13 10 0 09 Aug 2022
AMLB: an AutoML Benchmark Pieter Gijsbers Marcos L. P. Bueno Stefan Coors E. LeDell Sébastien Poirier Janek Thomas B. Bischl Joaquin Vanschoren 38 53 0 25 Jul 2022
Why do tree-based models still outperform deep learning on tabular data? Léo Grinsztajn Edouard Oyallon Gaël Varoquaux LMTD 35 356 0 18 Jul 2022
A novel evaluation methodology for supervised Feature Ranking algorithms Jeroen G. S. Overschie 16 0 0 09 Jul 2022
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets Charles Moussa Jan N. van Rijn Thomas Bäck Vedran Dunjko 27 12 0 20 Jun 2022
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization Zhen Wang Weirui Kuang Ce Zhang Bolin Ding Yaliang Li FedML 25 13 0 08 Jun 2022
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning Talip Uçar Ehsan Hajiramezanali Lindsay Edwards LMTD SSL 30 124 0 08 Oct 2021
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO Katharina Eggensperger Philip Muller Neeratyoy Mallik Matthias Feurer René Sass Aaron Klein Noor H. Awad Marius Lindauer Frank Hutter 46 100 0 14 Sep 2021
Test for non-negligible adverse shifts Vathy M. Kamulete 15 3 0 07 Jul 2021
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption Dara Bahri Heinrich Jiang Yi Tay Donald Metzler SSL 19 163 0 29 Jun 2021
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter 35 266 0 08 Jul 2020
Solving Constrained CASH Problems with ADMM Parikshit Ram Sijia Liu Deepak Vijaykeerthi Dakuo Wang Djallel Bouneffouf Gregory Bramble Horst Samulowitz Alexander G. Gray 23 3 0 17 Jun 2020
Model-agnostic Feature Importance and Effects with Dependent Features -- A Conditional Subgroup Approach Christoph Molnar Gunnar Konig B. Bischl Giuseppe Casalicchio 31 77 0 08 Jun 2020
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data Nick Erickson Jonas W. Mueller Alexander Shirkov Hang Zhang Pedro Larroy Mu Li Alex Smola LMTD 97 607 0 13 Mar 2020
OpenML-Python: an extensible Python API for OpenML Matthias Feurer Jan N. van Rijn Arlind Kadra Pieter Gijsbers Neeratyoy Mallik Sahithya Ravi Andreas Müller Joaquin Vanschoren Frank Hutter ELM GP 20 87 0 06 Nov 2019
The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development Micah J. Smith Carles Sala Cladellas James Max Kanter K. Veeramachaneni 22 49 0 22 May 2019
Benchmark and Survey of Automated Machine Learning Frameworks Marc-André Zöller Marco F. Huber 25 86 0 26 Apr 2019
Hyperparameters and Tuning Strategies for Random Forest Philipp Probst Marvin N. Wright A. Boulesteix 19 1,351 0 10 Apr 2018