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Improved Adversarial Training via Learned Optimizer

Improved Adversarial Training via Learned Optimizer

25 April 2020
Yuanhao Xiong
Cho-Jui Hsieh
    AAML
ArXivPDFHTML

Papers citing "Improved Adversarial Training via Learned Optimizer"

13 / 13 papers shown
Title
Generalizable Black-Box Adversarial Attack with Meta Learning
Generalizable Black-Box Adversarial Attack with Meta Learning
Fei Yin
Yong Zhang
Baoyuan Wu
Yan Feng
Jingyi Zhang
Yanbo Fan
Yujiu Yang
AAML
29
27
0
01 Jan 2023
VeLO: Training Versatile Learned Optimizers by Scaling Up
VeLO: Training Versatile Learned Optimizers by Scaling Up
Luke Metz
James Harrison
C. Freeman
Amil Merchant
Lucas Beyer
...
Naman Agrawal
Ben Poole
Igor Mordatch
Adam Roberts
Jascha Narain Sohl-Dickstein
35
60
0
17 Nov 2022
PointCAT: Contrastive Adversarial Training for Robust Point Cloud
  Recognition
PointCAT: Contrastive Adversarial Training for Robust Point Cloud Recognition
Qidong Huang
Xiaoyi Dong
Dongdong Chen
Hang Zhou
Weiming Zhang
Kui Zhang
Gang Hua
Nenghai Yu
3DPC
32
12
0
16 Sep 2022
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and
  Theoretical Analysis
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis
Taha Belkhouja
Yan Yan
J. Doppa
OOD
AI4TS
30
9
0
09 Jul 2022
Practical tradeoffs between memory, compute, and performance in learned
  optimizers
Practical tradeoffs between memory, compute, and performance in learned optimizers
Luke Metz
C. Freeman
James Harrison
Niru Maheswaranathan
Jascha Narain Sohl-Dickstein
41
32
0
22 Mar 2022
Learning for Robust Combinatorial Optimization: Algorithm and
  Application
Learning for Robust Combinatorial Optimization: Algorithm and Application
Zhihui Shao
Jianyi Yang
Cong Shen
Shaolei Ren
38
6
0
20 Dec 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based
  Adversarial Attacks
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
Maksym Yatsura
J. H. Metzen
Matthias Hein
OOD
26
14
0
02 Nov 2021
Learning to Optimize: A Primer and A Benchmark
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen
Xiaohan Chen
Wuyang Chen
Howard Heaton
Jialin Liu
Zhangyang Wang
W. Yin
54
225
0
23 Mar 2021
Architectural Adversarial Robustness: The Case for Deep Pursuit
Architectural Adversarial Robustness: The Case for Deep Pursuit
George Cazenavette
Calvin Murdock
Simon Lucey
AAML
34
23
0
29 Nov 2020
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Minhao Cheng
Simranjit Singh
Patrick H. Chen
Pin-Yu Chen
Sijia Liu
Cho-Jui Hsieh
AAML
126
219
0
24 Sep 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
383
11,700
0
09 Mar 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
296
3,112
0
04 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,842
0
08 Jul 2016
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