Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1902.01086
Cited By
v1
v2 (latest)
Computational Limitations in Robust Classification and Win-Win Results
4 February 2019
Akshay Degwekar
Preetum Nakkiran
Vinod Vaikuntanathan
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Computational Limitations in Robust Classification and Win-Win Results"
26 / 26 papers shown
On the Computability of Robust PAC Learning
Annual Conference Computational Learning Theory (COLT), 2024
Pascale Gourdeau
Tosca Lechner
Ruth Urner
434
6
0
14 Jun 2024
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness
ACM Computing Surveys (ACM Comput. Surv.), 2023
Peiyu Xiong
Michael W. Tegegn
Jaskeerat Singh Sarin
Shubhraneel Pal
Julia Rubin
SILM
AAML
420
16
0
17 Mar 2023
The Consistency of Adversarial Training for Binary Classification
Natalie Frank
Jonathan Niles-Weed
AAML
295
5
0
18 Jun 2022
Deconstructing Distributions: A Pointwise Framework of Learning
International Conference on Learning Representations (ICLR), 2022
Gal Kaplun
Nikhil Ghosh
Saurabh Garg
Boaz Barak
Preetum Nakkiran
OOD
254
24
0
20 Feb 2022
On the Existence of the Adversarial Bayes Classifier (Extended Version)
Pranjal Awasthi
Natalie Frank
M. Mohri
473
28
0
03 Dec 2021
A Law of Robustness for Weight-bounded Neural Networks
Hisham Husain
Borja Balle
232
2
0
16 Feb 2021
Robust and Private Learning of Halfspaces
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
Thao Nguyen
281
11
0
30 Nov 2020
A law of robustness for two-layers neural networks
Sébastien Bubeck
Yuanzhi Li
Dheeraj M. Nagaraj
407
63
0
30 Sep 2020
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise
Neural Information Processing Systems (NeurIPS), 2020
Ilias Diakonikolas
D. Kane
Pasin Manurangsi
293
23
0
30 Jul 2020
Adversarial Examples and Metrics
Nico Döttling
Kathrin Grosse
Michael Backes
Ian Molloy
AAML
224
0
0
14 Jul 2020
How benign is benign overfitting?
International Conference on Learning Representations (ICLR), 2020
Amartya Sanyal
P. Dokania
Varun Kanade
Juil Sock
NoLa
AAML
214
61
0
08 Jul 2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Zhun Deng
Linjun Zhang
Amirata Ghorbani
James Zou
239
32
0
15 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks
Neural Information Processing Systems (NeurIPS), 2020
Harshay Shah
Kaustav Tamuly
Aditi Raghunathan
Prateek Jain
Praneeth Netrapalli
AAML
427
436
0
13 Jun 2020
Depth-2 Neural Networks Under a Data-Poisoning Attack
Neurocomputing (Neurocomputing), 2020
Sayar Karmakar
Anirbit Mukherjee
Ramchandran Muthukumar
387
10
0
04 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
International Conference on Machine Learning (ICML), 2020
Pranjal Awasthi
Natalie Frank
M. Mohri
AAML
270
65
0
28 Apr 2020
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks
Neural Information Processing Systems (NeurIPS), 2020
Samuel Deng
Sanjam Garg
S. Jha
Saeed Mahloujifar
Mohammad Mahmoody
Abhradeep Thakurta
255
3
0
26 Mar 2020
Adversarially Robust Low Dimensional Representations
Annual Conference Computational Learning Theory (COLT), 2019
Pranjal Awasthi
Vaggos Chatziafratis
Xue Chen
Aravindan Vijayaraghavan
AAML
OOD
405
12
0
29 Nov 2019
Adaptive versus Standard Descent Methods and Robustness Against Adversarial Examples
Marc Khoury
AAML
262
1
0
09 Nov 2019
On the Hardness of Robust Classification
Pascale Gourdeau
Varun Kanade
Marta Z. Kwiatkowska
J. Worrell
182
44
0
12 Sep 2019
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin
Neural Information Processing Systems (NeurIPS), 2019
Ilias Diakonikolas
D. Kane
Pasin Manurangsi
239
20
0
29 Aug 2019
Computational Concentration of Measure: Optimal Bounds, Reductions, and More
ACM-SIAM Symposium on Discrete Algorithms (SODA), 2019
O. Etesami
Saeed Mahloujifar
Mohammad Mahmoody
277
16
0
11 Jul 2019
Lower Bounds for Adversarially Robust PAC Learning
International Conference on Machine Learning and Applications (ICMLA), 2019
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
305
27
0
13 Jun 2019
Unlabeled Data Improves Adversarial Robustness
Neural Information Processing Systems (NeurIPS), 2019
Y. Carmon
Aditi Raghunathan
Ludwig Schmidt
Abigail Z. Jacobs
John C. Duchi
609
801
0
31 May 2019
Adversarially Robust Learning Could Leverage Computational Hardness
International Conference on Algorithmic Learning Theory (ALT), 2019
Sanjam Garg
S. Jha
Saeed Mahloujifar
Mohammad Mahmoody
AAML
404
24
0
28 May 2019
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
1.0K
2,413
0
08 Feb 2019
Adversarial examples from computational constraints
Sébastien Bubeck
Eric Price
Ilya P. Razenshteyn
AAML
517
237
0
25 May 2018
1
Page 1 of 1
