Learning Curves for Decision Making in Supervised Machine Learning: A Survey

28 January 2022

Jan N. van Rijn

Papers citing "Learning Curves for Decision Making in Supervised Machine Learning: A Survey"

22 / 22 papers shown

Title
Meta-Learning from Learning Curves for Budget-Limited Algorithm Selection Manh Hung Nguyen Lisheng Sun-Hosoya Isabelle M Guyon 17 1 0 10 Oct 2024
MD tree: a model-diagnostic tree grown on loss landscape Yefan Zhou Jianlong Chen Qinxue Cao Konstantin Schürholt Yaoqing Yang 22 2 0 24 Jun 2024
Unraveling overoptimism and publication bias in ML-driven science Pouria Saidi Gautam Dasarathy Visar Berisha 23 2 0 23 May 2024
AI Competitions and Benchmarks: Dataset Development Romain Egele Julio C. S. Jacques Junior Jan N. van Rijn Isabelle M Guyon Xavier Baró Albert Clapés Prasanna Balaprakash Sergio Escalera T. Moeslund Jun Wan 27 0 0 15 Apr 2024
The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization Romain Egele Felix Mohr Tom Viering Prasanna Balaprakash 26 5 0 05 Apr 2024
Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting Hao Li Gopi Krishnan Rajbahadur Dayi Lin C. Bezemer Zhen Ming Jiang Jiang 13 25 0 18 Jan 2024
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks Steven Adriaensen Herilalaina Rakotoarison Samuel G. Müller Frank Hutter BDL 21 18 0 31 Oct 2023
Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning Joseph Giovanelli Alexander Tornede Tanja Tornede Marius Lindauer 22 6 0 07 Sep 2023
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? Romain Egele Isabelle M Guyon Yixuan Sun Prasanna Balaprakash 22 2 0 28 Jul 2023
Multi-Fidelity Multi-Armed Bandits Revisited Xuchuang Wang Qingyun Wu Wei-Neng Chen John C. S. Lui 23 3 0 13 Jun 2023
Artificial intelligence to advance Earth observation: a perspective D. Tuia Konrad Schindler Begum Demir Gustau Camps-Valls Xiao Xiang Zhu ... Mihai Datcu Jorge-Arnulfo Quiané-Ruiz Volker Markl Bertrand Le Saux Rochelle Schneider 18 10 0 15 May 2023
Optimizing Hyperparameters with Conformal Quantile Regression David Salinas Jacek Golebiowski Aaron Klein Matthias Seeger Cédric Archambeau 11 8 0 05 May 2023
Scaling Laws for Hyperparameter Optimization Arlind Kadra Maciej Janowski Martin Wistuba Josif Grabocka 15 8 0 01 Feb 2023
Learning to Rank Normalized Entropy Curves with Differentiable Window Transformation Hanyang Liu Shuai Yang Feng Qi Shuaiwen Wang 8 0 0 25 Jan 2023
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance Marco Loog T. Viering 16 1 0 25 Nov 2022
Meta-learning from Learning Curves Challenge: Lessons learned from the First Round and Design of the Second Round Manh Hung Nguyen Lisheng Sun Nathan Grinsztajn Isabelle M Guyon 10 1 0 04 Aug 2022
PASHA: Efficient HPO and NAS with Progressive Resource Allocation Ondrej Bohdal Lukas Balles Martin Wistuba B. Ermiş Cédric Archambeau Giovanni Zappella 19 12 0 14 Jul 2022
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets Charles Moussa Jan N. van Rijn Thomas Bäck Vedran Dunjko 19 11 0 20 Jun 2022
Towards Meta-learned Algorithm Selection using Implicit Fidelity Information Aditya Mohan Tim Ruhkopf Marius Lindauer FedML 11 3 0 07 Jun 2022
Fast and Informative Model Selection using Learning Curve Cross-Validation F. Mohr Jan N. van Rijn 17 28 0 27 Nov 2021
The Shape of Learning Curves: a Review T. Viering Marco Loog 11 119 0 19 Mar 2021
Recommending Training Set Sizes for Classification Phillip T. Koshute Jared Zook I. Mcculloh 8 4 0 16 Feb 2021