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Being Robust (in High Dimensions) Can Be Practical

Being Robust (in High Dimensions) Can Be Practical

2 March 2017
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jerry Li
Ankur Moitra
Alistair Stewart
ArXivPDFHTML

Papers citing "Being Robust (in High Dimensions) Can Be Practical"

50 / 177 papers shown
Title
Towards Trustworthy Federated Learning with Untrusted Participants
Towards Trustworthy Federated Learning with Untrusted Participants
Youssef Allouah
R. Guerraoui
John Stephan
FedML
65
0
0
03 May 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas
Giannis Iakovidis
D. Kane
Thanasis Pittas
87
0
0
20 Feb 2025
Optimal Rates for Robust Stochastic Convex Optimization
Optimal Rates for Robust Stochastic Convex Optimization
Changyu Gao
Andrew Lowy
Xingyu Zhou
Stephen J. Wright
81
0
0
15 Dec 2024
SoS Certifiability of Subgaussian Distributions and its Algorithmic
  Applications
SoS Certifiability of Subgaussian Distributions and its Algorithmic Applications
Ilias Diakonikolas
Samuel B. Hopkins
Ankit Pensia
Stefan Tiegel
51
3
0
28 Oct 2024
Efficient Statistics With Unknown Truncation, Polynomial Time
  Algorithms, Beyond Gaussians
Efficient Statistics With Unknown Truncation, Polynomial Time Algorithms, Beyond Gaussians
Jane H. Lee
Anay Mehrotra
Manolis Zampetakis
35
1
0
02 Oct 2024
Distribution Learnability and Robustness
Distribution Learnability and Robustness
Shai Ben-David
Alex Bie
Gautam Kamath
Tosca Lechner
39
2
0
25 Jun 2024
Robust Distribution Learning with Local and Global Adversarial
  Corruptions
Robust Distribution Learning with Local and Global Adversarial Corruptions
Sloan Nietert
Ziv Goldfeld
Soroosh Shafiee
OOD
38
0
0
10 Jun 2024
A Huber Loss Minimization Approach to Mean Estimation under User-level
  Differential Privacy
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy
Puning Zhao
Lifeng Lai
Li Shen
Qingming Li
Xiaogang Xu
Zhe Liu
55
7
0
22 May 2024
Robust Second-Order Nonconvex Optimization and Its Application to Low
  Rank Matrix Sensing
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
Shuyao Li
Yu Cheng
Ilias Diakonikolas
Jelena Diakonikolas
Rong Ge
Stephen J. Wright
49
2
0
12 Mar 2024
Corruption-Robust Offline Two-Player Zero-Sum Markov Games
Corruption-Robust Offline Two-Player Zero-Sum Markov Games
Andi Nika
Debmalya Mandal
Adish Singla
Goran Radanović
OffRL
34
2
0
04 Mar 2024
On the Byzantine-Resilience of Distillation-Based Federated Learning
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux
Max Zimmer
Sebastian Pokutta
AAML
62
1
0
19 Feb 2024
Corruption Robust Offline Reinforcement Learning with Human Feedback
Corruption Robust Offline Reinforcement Learning with Human Feedback
Debmalya Mandal
Andi Nika
Parameswaran Kamalaruban
Adish Singla
Goran Radanović
OffRL
38
9
0
09 Feb 2024
Attacking Byzantine Robust Aggregation in High Dimensions
Attacking Byzantine Robust Aggregation in High Dimensions
Sarthak Choudhary
Aashish Kolluri
Prateek Saxena
AAML
45
1
0
22 Dec 2023
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean
  Estimation and Linear Regression
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
Ilias Diakonikolas
Daniel M. Kane
Ankit Pensia
Thanasis Pittas
40
2
0
04 Dec 2023
Outlier-Robust Wasserstein DRO
Outlier-Robust Wasserstein DRO
Sloan Nietert
Ziv Goldfeld
Soroosh Shafiee
41
9
0
09 Nov 2023
Byzantine-Resilient Federated PCA and Low Rank Column-wise Sensing
Byzantine-Resilient Federated PCA and Low Rank Column-wise Sensing
Ankit Pratap Singh
Namrata Vaswani
39
0
0
25 Sep 2023
A Huber Loss Minimization Approach to Byzantine Robust Federated
  Learning
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning
Puning Zhao
Fei Yu
Zhiguo Wan
FedML
48
13
0
24 Aug 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of
  Byzantine Attackers
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers
Puning Zhao
Zhiguo Wan
OOD
FedML
50
4
0
25 Jul 2023
A Survey of What to Share in Federated Learning: Perspectives on Model
  Utility, Privacy Leakage, and Communication Efficiency
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
Jiawei Shao
Zijian Li
Wenqiang Sun
Tailin Zhou
Yuchang Sun
Lumin Liu
Zehong Lin
Yuyi Mao
Jun Zhang
FedML
50
23
0
20 Jul 2023
Robust Nonparametric Regression under Poisoning Attack
Robust Nonparametric Regression under Poisoning Attack
Puning Zhao
Z. Wan
AAML
28
8
0
26 May 2023
Robust Sparse Mean Estimation via Incremental Learning
Robust Sparse Mean Estimation via Incremental Learning
Jianhao Ma
Ruidi Chen
Yinghui He
S. Fattahi
Wei Hu
41
0
0
24 May 2023
On the Optimal Batch Size for Byzantine-Robust Distributed Learning
On the Optimal Batch Size for Byzantine-Robust Distributed Learning
Yi-Rui Yang
Chang-Wei Shi
Wu-Jun Li
FedML
AAML
32
0
0
23 May 2023
Learning Mixtures of Gaussians with Censored Data
Learning Mixtures of Gaussians with Censored Data
W. Tai
Bryon Aragam
26
1
0
06 May 2023
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA
Ilias Diakonikolas
D. Kane
Ankit Pensia
Thanasis Pittas
OOD
36
10
0
04 May 2023
Protecting Federated Learning from Extreme Model Poisoning Attacks via
  Multidimensional Time Series Anomaly Detection
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection
Edoardo Gabrielli
Dimitri Belli
Vittorio Miori
Gabriele Tolomei
AAML
13
4
0
29 Mar 2023
Robustifying likelihoods by optimistically re-weighting data
Robustifying likelihoods by optimistically re-weighting data
Miheer Dewaskar
Christopher Tosh
Jeremias Knoblauch
David B. Dunson
32
5
0
19 Mar 2023
Robust Mean Estimation Without Moments for Symmetric Distributions
Robust Mean Estimation Without Moments for Symmetric Distributions
Gleb Novikov
David Steurer
Stefan Tiegel
OOD
31
0
0
21 Feb 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning
On the Privacy-Robustness-Utility Trilemma in Distributed Learning
Youssef Allouah
R. Guerraoui
Nirupam Gupta
Rafael Pinot
John Stephan
FedML
26
21
0
09 Feb 2023
From Robustness to Privacy and Back
From Robustness to Privacy and Back
Hilal Asi
Jonathan R. Ullman
Lydia Zakynthinou
44
27
0
03 Feb 2023
Near Optimal Private and Robust Linear Regression
Near Optimal Private and Robust Linear Regression
Xiyang Liu
Prateek Jain
Weihao Kong
Sewoong Oh
A. Suggala
41
9
0
30 Jan 2023
Statistically Optimal Robust Mean and Covariance Estimation for
  Anisotropic Gaussians
Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians
A. Minasyan
Nikita Zhivotovskiy
36
9
0
21 Jan 2023
Robustifying Markowitz
Robustifying Markowitz
W. Hardle
Yegor Klochkov
Alla Petukhina
Nikita Zhivotovskiy
19
7
0
28 Dec 2022
Robustness Implies Privacy in Statistical Estimation
Robustness Implies Privacy in Statistical Estimation
Samuel B. Hopkins
Gautam Kamath
Mahbod Majid
Shyam Narayanan
23
50
0
09 Dec 2022
Efficient List-Decodable Regression using Batches
Efficient List-Decodable Regression using Batches
Abhimanyu Das
Ayush Jain
Weihao Kong
Rajat Sen
30
4
0
23 Nov 2022
Knowledge Distillation for Federated Learning: a Practical Guide
Knowledge Distillation for Federated Learning: a Practical Guide
Alessio Mora
Irene Tenison
Paolo Bellavista
Irina Rish
FedML
25
17
0
09 Nov 2022
Towards Fair Classification against Poisoning Attacks
Towards Fair Classification against Poisoning Attacks
Han Xu
Xiaorui Liu
Yuxuan Wan
Jiliang Tang
21
2
0
18 Oct 2022
Statistical, Robustness, and Computational Guarantees for Sliced
  Wasserstein Distances
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
Sloan Nietert
Ritwik Sadhu
Ziv Goldfeld
Kengo Kato
40
37
0
17 Oct 2022
A Survey on Heterogeneous Federated Learning
A Survey on Heterogeneous Federated Learning
Dashan Gao
Xin Yao
Qian Yang
FedML
37
58
0
10 Oct 2022
Renyi Differential Privacy of Propose-Test-Release and Applications to
  Private and Robust Machine Learning
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning
Jiachen T. Wang
Saeed Mahloujifar
Shouda Wang
R. Jia
Prateek Mittal
AAML
42
5
0
16 Sep 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients
Outlier Robust and Sparse Estimation of Linear Regression Coefficients
Takeyuki Sasai
Hironori Fujisawa
35
4
0
24 Aug 2022
Minimax Rates for Robust Community Detection
Minimax Rates for Robust Community Detection
Allen Liu
Ankur Moitra
27
13
0
25 Jul 2022
Robust and Sparse Estimation of Linear Regression Coefficients with
  Heavy-tailed Noises and Covariates
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates
Takeyuki Sasai
26
4
0
15 Jun 2022
Robust Sparse Mean Estimation via Sum of Squares
Robust Sparse Mean Estimation via Sum of Squares
Ilias Diakonikolas
D. Kane
Sushrut Karmalkar
Ankit Pensia
Thanasis Pittas
30
21
0
07 Jun 2022
Byzantine-Robust Online and Offline Distributed Reinforcement Learning
Byzantine-Robust Online and Offline Distributed Reinforcement Learning
Yiding Chen
Xuezhou Zhang
Kaipeng Zhang
Mengdi Wang
Xiaojin Zhu
OffRL
26
16
0
01 Jun 2022
List-Decodable Sparse Mean Estimation
List-Decodable Sparse Mean Estimation
Shiwei Zeng
Jie Shen
32
9
0
28 May 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and
  Privacy Guarantees
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees
Banghua Zhu
Lun Wang
Qi Pang
Shuai Wang
Jiantao Jiao
D. Song
Michael I. Jordan
FedML
98
30
0
24 May 2022
Towards a Defense Against Federated Backdoor Attacks Under Continuous
  Training
Towards a Defense Against Federated Backdoor Attacks Under Continuous Training
Shuai Wang
J. Hayase
Giulia Fanti
Sewoong Oh
FedML
36
5
0
24 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey
Djamila Bouhata
Hamouma Moumen
Moumen Hamouma
Ahcène Bounceur
AI4CE
31
7
0
05 May 2022
Streaming Algorithms for High-Dimensional Robust Statistics
Streaming Algorithms for High-Dimensional Robust Statistics
Ilias Diakonikolas
D. Kane
Ankit Pensia
Thanasis Pittas
24
21
0
26 Apr 2022
Nearly minimax robust estimator of the mean vector by iterative spectral
  dimension reduction
Nearly minimax robust estimator of the mean vector by iterative spectral dimension reduction
A. Bateni
A. Minasyan
A. Dalalyan
34
2
0
05 Apr 2022
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