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Adversarial Risk Bounds via Function Transformation

Adversarial Risk Bounds via Function Transformation

22 October 2018
Justin Khim
Po-Ling Loh
    AAML
ArXivPDFHTML

Papers citing "Adversarial Risk Bounds via Function Transformation"

14 / 14 papers shown
Title
Robust Empirical Risk Minimization with Tolerance
Robust Empirical Risk Minimization with Tolerance
Robi Bhattacharjee
Max Hopkins
Akash Kumar
Hantao Yu
Kamalika Chaudhuri
OOD
28
8
0
02 Oct 2022
Transductive Robust Learning Guarantees
Transductive Robust Learning Guarantees
Omar Montasser
Steve Hanneke
Nathan Srebro
16
13
0
20 Oct 2021
Attack Transferability Characterization for Adversarially Robust
  Multi-label Classification
Attack Transferability Characterization for Adversarially Robust Multi-label Classification
Zhuo Yang
Yufei Han
Xiangliang Zhang
AAML
23
4
0
29 Jun 2021
Sharp Statistical Guarantees for Adversarially Robust Gaussian
  Classification
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
Chen Dan
Yuting Wei
Pradeep Ravikumar
24
45
0
29 Jun 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise
Efficiently Learning Adversarially Robust Halfspaces with Noise
Omar Montasser
Surbhi Goel
Ilias Diakonikolas
Nathan Srebro
29
32
0
15 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural
  Networks
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Pranjal Awasthi
Natalie Frank
M. Mohri
AAML
28
56
0
28 Apr 2020
The Curious Case of Adversarially Robust Models: More Data Can Help,
  Double Descend, or Hurt Generalization
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization
Yifei Min
Lin Chen
Amin Karbasi
AAML
31
69
0
25 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust
  and Standard Models
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models
Lin Chen
Yifei Min
Mingrui Zhang
Amin Karbasi
OOD
27
64
0
11 Feb 2020
Improved Sample Complexities for Deep Networks and Robust Classification
  via an All-Layer Margin
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin
Colin Wei
Tengyu Ma
AAML
OOD
36
85
0
09 Oct 2019
Adversarial Training Can Hurt Generalization
Adversarial Training Can Hurt Generalization
Aditi Raghunathan
Sang Michael Xie
Fanny Yang
John C. Duchi
Percy Liang
13
239
0
14 Jun 2019
Lower Bounds for Adversarially Robust PAC Learning
Lower Bounds for Adversarially Robust PAC Learning
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
19
26
0
13 Jun 2019
Adversarially Robust Learning Could Leverage Computational Hardness
Adversarially Robust Learning Could Leverage Computational Hardness
Sanjam Garg
S. Jha
Saeed Mahloujifar
Mohammad Mahmoody
AAML
16
24
0
28 May 2019
Theoretical Analysis of Adversarial Learning: A Minimax Approach
Theoretical Analysis of Adversarial Learning: A Minimax Approach
Zhuozhuo Tu
Jingwei Zhang
Dacheng Tao
AAML
13
68
0
13 Nov 2018
Adversarial examples from computational constraints
Adversarial examples from computational constraints
Sébastien Bubeck
Eric Price
Ilya P. Razenshteyn
AAML
65
230
0
25 May 2018
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