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How Much More Data Do I Need? Estimating Requirements for Downstream Tasks

4 July 2022

Sanja Fidler

Papers citing "How Much More Data Do I Need? Estimating Requirements for Downstream Tasks"

23 / 23 papers shown

Title
ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesis Onkar Susladkar Gayatri Deshmukh Yalcin Tur Gorkhem Durak Ulas Bagci MedIm 227 0 0 08 May 2025
Breaking Neural Network Scaling Laws with Modularity Akhilan Boopathy Sunshine Jiang William Yue Jaedong Hwang Abhiram Iyer Ila Fiete OOD 115 2 0 09 Sep 2024
Exploring the Limits of Large Scale Pre-training Samira Abnar Mostafa Dehghani Behnam Neyshabur Hanie Sedghi AI4CE 101 119 0 05 Oct 2021
Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories Fait Poms Vishnu Sarukkai Ravi Teja Mullapudi N. Sohoni W. Mark Deva Ramanan Kayvon Fatahalian 38 9 0 13 Sep 2021
Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection Ismail Elezi Zhiding Yu Anima Anandkumar Laura Leal-Taixe J. Álvarez ObjD 79 41 0 22 Jun 2021
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach Rafid Mahmood Sanja Fidler M. Law 74 37 0 05 Jun 2021
FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection Tai Wang Xinge Zhu Jiangmiao Pang Dahua Lin 3DPC 109 602 0 22 Apr 2021
The Shape of Learning Curves: a Review T. Viering Marco Loog 69 133 0 19 Mar 2021
Explaining Neural Scaling Laws Yasaman Bahri Ethan Dyer Jared Kaplan Jaehoon Lee Utkarsh Sharma 78 269 0 12 Feb 2021
Learning Curve Theory Marcus Hutter 218 64 0 08 Feb 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning Yiding Jiang Pierre Foret Scott Yak Daniel M. Roy H. Mobahi Gintare Karolina Dziugaite Samy Bengio Suriya Gunasekar Isabelle M Guyon Behnam Neyshabur Google Research OOD 64 55 0 14 Dec 2020
Learning Curves for Analysis of Deep Networks Derek Hoiem Tanmay Gupta Zhizhong Li Michal Shlapentokh-Rothman 75 26 0 21 Oct 2020
Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D Jonah Philion Sanja Fidler 100 1,055 0 13 Aug 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 638 4,921 0 23 Jan 2020
A Constructive Prediction of the Generalization Error Across Scales Jonathan S. Rosenfeld Amir Rosenfeld Yonatan Belinkov Nir Shavit 105 215 0 27 Sep 2019
Learning Loss for Active Learning Donggeun Yoo In So Kweon UQCV 85 663 0 09 May 2019
Variational Adversarial Active Learning Samarth Sinha Sayna Ebrahimi Trevor Darrell GAN DRL VLM SSL 140 579 0 31 Mar 2019
nuScenes: A multimodal dataset for autonomous driving Holger Caesar Varun Bankiti Alex H. Lang Sourabh Vora Venice Erin Liong Qiang Xu Anush Krishnan Yuxin Pan G. Baldan Oscar Beijbom 3DPC 301 5,786 0 26 Mar 2019
Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++ David Acuna Huan Ling Amlan Kar Sanja Fidler 103 403 0 26 Mar 2018
Deep Learning Scaling is Predictable, Empirically Joel Hestness Sharan Narang Newsha Ardalani G. Diamos Heewoo Jun Hassan Kianinejad Md. Mostofa Ali Patwary Yang Yang Yanqi Zhou 112 744 0 01 Dec 2017
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun Abhinav Shrivastava Saurabh Singh Abhinav Gupta VLM 207 2,407 0 10 Jul 2017
Rethinking Atrous Convolution for Semantic Image Segmentation Liang-Chieh Chen George Papandreou Florian Schroff Hartwig Adam SSeg 234 8,491 0 17 Jun 2017
Wide Residual Networks Sergey Zagoruyko N. Komodakis 356 8,002 0 23 May 2016