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Do We Train on Test Data? Purging CIFAR of Near-Duplicates

Do We Train on Test Data? Purging CIFAR of Near-Duplicates

1 February 2019
Björn Barz
Joachim Denzler
ArXivPDFHTML

Papers citing "Do We Train on Test Data? Purging CIFAR of Near-Duplicates"

26 / 26 papers shown
Title
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Alireza Aghabagherloo
Aydin Abadi
Sumanta Sarkar
Vishnu Asutosh Dasu
Bart Preneel
AAML
65
0
0
01 Apr 2025
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Luca Arnaboldi
Yatin Dandi
Florent Krzakala
Luca Pesce
Ludovic Stephan
70
12
0
24 May 2024
Automated Program Repair: Emerging trends pose and expose problems for
  benchmarks
Automated Program Repair: Emerging trends pose and expose problems for benchmarks
J. Renzullo
Pemma Reiter
Westley Weimer
Stephanie Forrest
42
1
0
08 May 2024
Tune without Validation: Searching for Learning Rate and Weight Decay on
  Training Sets
Tune without Validation: Searching for Learning Rate and Weight Decay on Training Sets
Lorenzo Brigato
Stavroula Mougiakakou
45
0
0
08 Mar 2024
Benchmarking Pretrained Vision Embeddings for Near- and Duplicate
  Detection in Medical Images
Benchmarking Pretrained Vision Embeddings for Near- and Duplicate Detection in Medical Images
Tuan Truong
Farnaz Khun Jush
Matthias Lenga
34
2
0
12 Dec 2023
Data-Efficient Energy-Aware Participant Selection for UAV-Enabled
  Federated Learning
Data-Efficient Energy-Aware Participant Selection for UAV-Enabled Federated Learning
Youssra Cheriguene
Wael Jaafar
Kerrache Chaker Abdelaziz
H. Yanikomeroglu
Fatima Zohra Bousbaa
N. Lagraa
FedML
44
1
0
14 Aug 2023
On Evaluation of Document Classification using RVL-CDIP
On Evaluation of Document Classification using RVL-CDIP
Stefan Larson
Gordon Lim
Kevin Leach
39
3
0
21 Jun 2023
How Effective Are Neural Networks for Fixing Security Vulnerabilities
How Effective Are Neural Networks for Fixing Security Vulnerabilities
Yi Wu
Nan Jiang
H. Pham
Thibaud Lutellier
Jordan Davis
Lin Tan
Petr Babkin
Sameena Shah
AAML
21
79
0
29 May 2023
Infinite Class Mixup
Infinite Class Mixup
Thomas Mensink
Pascal Mettes
31
2
0
17 May 2023
Do We Train on Test Data? The Impact of Near-Duplicates on License Plate
  Recognition
Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognition
Rayson Laroca
Valter Estevam
A. Britto
Rodrigo Minetto
David Menotti
30
10
0
10 Apr 2023
Image Classification with Small Datasets: Overview and Benchmark
Image Classification with Small Datasets: Overview and Benchmark
Lorenzo Brigato
Björn Barz
Luca Iocchi
Joachim Denzler
VLM
30
17
0
23 Dec 2022
A Pareto-optimal compositional energy-based model for sampling and
  optimization of protein sequences
A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences
Natavsa Tagasovska
Nathan C. Frey
Andreas Loukas
I. Hotzel
J. Lafrance-Vanasse
...
A. Rajpal
Richard Bonneau
Kyunghyun Cho
Stephen Ra
Vladimir Gligorijević
18
11
0
19 Oct 2022
Unsupervised visualization of image datasets using contrastive learning
Unsupervised visualization of image datasets using contrastive learning
Jan Boehm
Philipp Berens
D. Kobak
SSL
26
15
0
18 Oct 2022
Bugs in the Data: How ImageNet Misrepresents Biodiversity
Bugs in the Data: How ImageNet Misrepresents Biodiversity
A. Luccioni
David Rolnick
21
43
0
24 Aug 2022
When does dough become a bagel? Analyzing the remaining mistakes on
  ImageNet
When does dough become a bagel? Analyzing the remaining mistakes on ImageNet
Vijay Vasudevan
Benjamin Caine
Raphael Gontijo-Lopes
Sara Fridovich-Keil
Rebecca Roelofs
VLM
UQCV
48
57
0
09 May 2022
A Siren Song of Open Source Reproducibility
A Siren Song of Open Source Reproducibility
Edward Raff
Andrew L. Farris
16
9
0
09 Apr 2022
Datamodels: Predicting Predictions from Training Data
Datamodels: Predicting Predictions from Training Data
Andrew Ilyas
Sung Min Park
Logan Engstrom
Guillaume Leclerc
A. Madry
TDI
47
131
0
01 Feb 2022
A Framework for Cluster and Classifier Evaluation in the Absence of
  Reference Labels
A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels
R. Joyce
Edward Raff
Charles K. Nicholas
48
16
0
23 Sep 2021
Tune It or Don't Use It: Benchmarking Data-Efficient Image
  Classification
Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification
Lorenzo Brigato
Björn Barz
Luca Iocchi
Joachim Denzler
35
16
0
30 Aug 2021
On Memorization in Probabilistic Deep Generative Models
On Memorization in Probabilistic Deep Generative Models
G. V. D. Burg
Christopher K. I. Williams
TDI
25
59
0
06 Jun 2021
FSD50K: An Open Dataset of Human-Labeled Sound Events
FSD50K: An Open Dataset of Human-Labeled Sound Events
Eduardo Fonseca
Xavier Favory
Jordi Pons
F. Font
Xavier Serra
26
436
0
01 Oct 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
46
441
0
09 Aug 2020
Are we done with ImageNet?
Are we done with ImageNet?
Lucas Beyer
Olivier J. Hénaff
Alexander Kolesnikov
Xiaohua Zhai
Aaron van den Oord
VLM
19
397
0
12 Jun 2020
The Curious Case of Convex Neural Networks
The Curious Case of Convex Neural Networks
S. Sivaprasad
Ankur Singh
Naresh Manwani
Vineet Gandhi
46
27
0
09 Jun 2020
Self-Distillation as Instance-Specific Label Smoothing
Self-Distillation as Instance-Specific Label Smoothing
Zhilu Zhang
M. Sabuncu
20
116
0
09 Jun 2020
Big Transfer (BiT): General Visual Representation Learning
Big Transfer (BiT): General Visual Representation Learning
Alexander Kolesnikov
Lucas Beyer
Xiaohua Zhai
J. Puigcerver
Jessica Yung
Sylvain Gelly
N. Houlsby
MQ
106
1,183
0
24 Dec 2019
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