A Meta-Learning Approach to Predicting Performance and Data Requirements

A Meta-Learning Approach to Predicting Performance and Data Requirements

2 March 2023

Gurumurthy Swaminathan

Avinash Ravichandran

Hrayr Harutyunyan

Alessandro Achille

Bernt Schiele

Papers citing "A Meta-Learning Approach to Predicting Performance and Data Requirements"

9 / 9 papers shown

Title
Data Scaling Laws for End-to-End Autonomous Driving Alexander Naumann Xunjiang Gu Tolga Dimlioglu Mariusz Bojarski Alperen Degirmenci A. Popov Devansh Bisla Marco Pavone Urs Muller B. Ivanovic 46 0 0 06 Apr 2025
Scaling Laws for Downstream Task Performance in Machine Translation Berivan Isik Natalia Ponomareva Hussein Hazimeh Dimitris Paparas Sergei Vassilvitskii Sanmi Koyejo 105 23 0 24 Feb 2025
A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data Ethan Harvey Wansu Chen David M Kent Michael C. Hughes 11 1 0 29 Nov 2023
How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget Guy Hacohen D. Weinshall 8 8 0 06 Jun 2023
Scaling Laws for Hyperparameter Optimization Arlind Kadra Maciej Janowski Martin Wistuba Josif Grabocka 15 8 0 01 Feb 2023
Optimizing Data Collection for Machine Learning Rafid Mahmood James Lucas J. Álvarez Sanja Fidler M. Law 47 26 0 03 Oct 2022
Revisiting Neural Scaling Laws in Language and Vision Ibrahim M. Alabdulmohsin Behnam Neyshabur Xiaohua Zhai 148 101 0 13 Sep 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
CrowdHuman: A Benchmark for Detecting Human in a Crowd Shuai Shao Zijian Zhao Boxun Li Tete Xiao Gang Yu Xiangyu Zhang Jian-jun Sun 211 670 0 30 Apr 2018