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Deep Learning Through the Lens of Example Difficulty

Deep Learning Through the Lens of Example Difficulty

17 June 2021
R. Baldock
Hartmut Maennel
Behnam Neyshabur
ArXivPDFHTML

Papers citing "Deep Learning Through the Lens of Example Difficulty"

12 / 112 papers shown
Title
On the Impact of Hard Adversarial Instances on Overfitting in
  Adversarial Training
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
15
13
0
14 Dec 2021
Trivial or impossible -- dichotomous data difficulty masks model
  differences (on ImageNet and beyond)
Trivial or impossible -- dichotomous data difficulty masks model differences (on ImageNet and beyond)
Kristof Meding
Luca M. Schulze Buschoff
Robert Geirhos
Felix Wichmann
28
40
0
12 Oct 2021
Intriguing Properties of Input-dependent Randomized Smoothing
Intriguing Properties of Input-dependent Randomized Smoothing
Peter Súkeník
A. Kuvshinov
Stephan Günnemann
AAML
UQCV
14
21
0
11 Oct 2021
Exploring the Limits of Large Scale Pre-training
Exploring the Limits of Large Scale Pre-training
Samira Abnar
Mostafa Dehghani
Behnam Neyshabur
Hanie Sedghi
AI4CE
55
114
0
05 Oct 2021
The Impact of Reinitialization on Generalization in Convolutional Neural
  Networks
The Impact of Reinitialization on Generalization in Convolutional Neural Networks
Ibrahim M. Alabdulmohsin
Hartmut Maennel
Daniel Keysers
AI4CE
21
20
0
01 Sep 2021
A Tale Of Two Long Tails
A Tale Of Two Long Tails
Daniel D'souza
Zach Nussbaum
Chirag Agarwal
Sara Hooker
16
22
0
27 Jul 2021
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
11
432
0
15 Jul 2021
HODA: Hardness-Oriented Detection of Model Extraction Attacks
HODA: Hardness-Oriented Detection of Model Extraction Attacks
A. M. Sadeghzadeh
Amir Mohammad Sobhanian
F. Dehghan
R. Jalili
MIACV
17
7
0
21 Jun 2021
Interpretable Deep Learning: Interpretation, Interpretability,
  Trustworthiness, and Beyond
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond
Xuhong Li
Haoyi Xiong
Xingjian Li
Xuanyu Wu
Xiao Zhang
Ji Liu
Jiang Bian
Dejing Dou
AAML
FaML
XAI
HAI
15
315
0
19 Mar 2021
Estimating Example Difficulty Using Variance of Gradients
Estimating Example Difficulty Using Variance of Gradients
Chirag Agarwal
Daniel D'souza
Sara Hooker
208
107
0
26 Aug 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
281
2,888
0
15 Sep 2016
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