Learning Curve Extrapolation using Machine Learning - TU Delft
This study explores the extrapolation of learning curves, a crucial aspect in evaluating learner performance with varying dataset sample sizes. We use the Learning Curve Prior Fitted …
[2310.20447] Efficient Bayesian Learning Curve Extrapolation using ...
Oct 31, 2023 · We propose LC-PFN, a PFN trained to extrapolate 10 million artificial right-censored learning curves generated from a parametric prior proposed in prior art using …
LC-PFN: Efficient Bayesian Learning Curve Extrapolation using …
Dec 8, 2023 · In our paper, we propose LC-PFN, a novel method for Bayesian learning curve extrapolation. LC-PFN is a prior-data-fitted network (PFN), a transformer trained on synthetic …
Learning Learning Curves | Pattern Analysis and Applications
Jan 3, 2025 · Extrapolating learning curves can be useful for determining the performance gain with additional data. Parametric functions, that assume monotone behaviour of the curves, are …
Our basic approach is to t parametric models M to y1:n and use them to infer ym, with m > n. From a broad range of parametric models we selected ten that match the shape of learning …
Learning Curve Extrapolation Methods Across Extrapolation …
Apr 16, 2024 · Our main focus is on learning curve extrapolation methods that can be used in general, and which are usually tested on simple machine learning algorithms. In this section …
Learning Learning Curves | Pattern Analysis & Applications
Jan 3, 2025 · Extrapolating learning curves can be useful for determining the performance gain with additional data. Parametric functions, that assume monotone behaviour of the curves, are …
learning curve extrapolation, this thesis aims to answer the following research question: What are the benefits and limitations of using LC-PFN for learning curve ex-trapolation and how does it …
Architecture-Aware Learning Curve Extrapolation via Graph …
Dec 20, 2024 · Learning curve extrapolation predicts neural network performance from early training epochs and has been applied to accelerate AutoML, facilitating hyperparameter tuning …
Efficient Bayesian Learning Curve Extrapolation using Prior-Data...
Oct 21, 2022 · TL;DR: We show that Prior-data Fitted Networks (PFNs) compare favorably against MCMC for learning curve inference. Abstract: Learning curve extrapolation aims to …