ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2308.01189
  4. Cited By
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical
  Image Segmentation

Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation

2 August 2023
Yongkang He
Mingjin Chen
Zhi-Yi Yang
Yongyi Lu
ArXivPDFHTML

Papers citing "Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation"

16 / 16 papers shown
Title
Beyond neural scaling laws: beating power law scaling via data pruning
Beyond neural scaling laws: beating power law scaling via data pruning
Ben Sorscher
Robert Geirhos
Shashank Shekhar
Surya Ganguli
Ari S. Morcos
79
439
0
29 Jun 2022
Deep Learning on a Data Diet: Finding Important Examples Early in
  Training
Deep Learning on a Data Diet: Finding Important Examples Early in Training
Mansheej Paul
Surya Ganguli
Gintare Karolina Dziugaite
105
456
0
15 Jul 2021
Deep Learning Through the Lens of Example Difficulty
Deep Learning Through the Lens of Example Difficulty
R. Baldock
Hartmut Maennel
Behnam Neyshabur
72
160
0
17 Jun 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient
  Deep Model Training
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
Krishnateja Killamsetty
D. Sivasubramanian
Ganesh Ramakrishnan
A. De
Rishabh K. Iyer
OOD
122
200
0
27 Feb 2021
GLISTER: Generalization based Data Subset Selection for Efficient and
  Robust Learning
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning
Krishnateja Killamsetty
D. Sivasubramanian
Ganesh Ramakrishnan
Rishabh Iyer University of Texas at Dallas
58
208
0
19 Dec 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training
  Dynamics
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
Swabha Swayamdipta
Roy Schwartz
Nicholas Lourie
Yizhong Wang
Hannaneh Hajishirzi
Noah A. Smith
Yejin Choi
90
447
0
22 Sep 2020
Estimating Example Difficulty Using Variance of Gradients
Estimating Example Difficulty Using Variance of Gradients
Chirag Agarwal
Daniel D'souza
Sara Hooker
245
110
0
26 Aug 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via
  Influence Estimation
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
Vitaly Feldman
Chiyuan Zhang
TDI
132
459
0
09 Aug 2020
A Study of Gradient Variance in Deep Learning
A Study of Gradient Variance in Deep Learning
Fartash Faghri
David Duvenaud
David J. Fleet
Jimmy Ba
FedML
ODL
39
27
0
09 Jul 2020
Characterizing Structural Regularities of Labeled Data in
  Overparameterized Models
Characterizing Structural Regularities of Labeled Data in Overparameterized Models
Ziheng Jiang
Chiyuan Zhang
Kunal Talwar
Michael C. Mozer
TDI
56
102
0
08 Feb 2020
Selection via Proxy: Efficient Data Selection for Deep Learning
Selection via Proxy: Efficient Data Selection for Deep Learning
Cody Coleman
Christopher Yeh
Stephen Mussmann
Baharan Mirzasoleiman
Peter Bailis
Percy Liang
J. Leskovec
Matei A. Zaharia
73
345
0
26 Jun 2019
Let's Agree to Agree: Neural Networks Share Classification Order on Real
  Datasets
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets
Guy Hacohen
Leshem Choshen
D. Weinshall
AI4TS
OOD
54
57
0
26 May 2019
A large annotated medical image dataset for the development and
  evaluation of segmentation algorithms
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Amber L. Simpson
Michela Antonelli
Spyridon Bakas
Michel Bilello
Keyvan Farahani
...
M. McHugo
S. Napel
Eugene Vorontsov
Lena Maier-Hein
M. Jorge Cardoso
106
858
0
25 Feb 2019
An Empirical Study of Example Forgetting during Deep Neural Network
  Learning
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva
Alessandro Sordoni
Rémi Tachet des Combes
Adam Trischler
Yoshua Bengio
Geoffrey J. Gordon
107
732
0
12 Dec 2018
Active Bias: Training More Accurate Neural Networks by Emphasizing High
  Variance Samples
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples
Haw-Shiuan Chang
Erik Learned-Miller
Andrew McCallum
73
352
0
24 Apr 2017
Training Region-based Object Detectors with Online Hard Example Mining
Training Region-based Object Detectors with Online Hard Example Mining
Abhinav Shrivastava
Abhinav Gupta
Ross B. Girshick
ObjD
143
2,416
0
12 Apr 2016
1