Recent Advances in Algorithmic High-Dimensional Robust Statistics

14 November 2019

Papers citing "Recent Advances in Algorithmic High-Dimensional Robust Statistics"

50 / 146 papers shown

Title
Learning High-dimensional Gaussians from Censored Data Arnab Bhattacharyya C. Daskalakis Themis Gouleakis Yuhao Wang 95 0 0 28 Apr 2025
Geometric Median Matching for Robust k-Subset Selection from Noisy Data Anish Acharya Sujay Sanghavi Alexandros G. Dimakis Inderjit S Dhillon AAML 181 0 0 01 Apr 2025
Sample-Optimal Private Regression in Polynomial Time Prashanti Anderson Ainesh Bakshi Mahbod Majid Stefan Tiegel 41 0 0 31 Mar 2025
Geometric Median (GM) Matching for Robust Data Pruning Anish Acharya Inderjit S Dhillon Sujay Sanghavi AAML 139 0 0 20 Jan 2025
Optimal Rates for Robust Stochastic Convex Optimization Changyu Gao Andrew Lowy Xingyu Zhou Stephen J. Wright 129 0 0 15 Dec 2024
Robust high-dimensional Gaussian and bootstrap approximations for trimmed sample means Lucas Resende 86 1 0 29 Oct 2024
Perturb-and-Project: Differentially Private Similarities and Marginals Vincent Cohen-Addad Tommaso dÓrsi Alessandro Epasto Vahab Mirrokni Peilin Zhong 81 0 0 07 Jun 2024
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering Vincent Cohen-Addad Tommaso dÓrsi Aida Mousavifar 91 1 0 07 Jun 2024
Tolerant Algorithms for Learning with Arbitrary Covariate Shift Surbhi Goel Abhishek Shetty Konstantinos Stavropoulos Arsen Vasilyan OOD 83 3 0 04 Jun 2024
Robust Kernel Hypothesis Testing under Data Corruption Antonin Schrab Ilmun Kim 103 4 0 30 May 2024
Learning from Uncertain Data: From Possible Worlds to Possible Models Jiongli Zhu Su Feng Boris Glavic Babak Salimi 68 1 0 28 May 2024
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods Elita Lobo Harvineet Singh Marek Petrik Cynthia Rudin Himabindu Lakkaraju 73 3 0 06 Apr 2024
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 71 2 0 12 Mar 2024
Corruption Robust Offline Reinforcement Learning with Human Feedback Debmalya Mandal Andi Nika Parameswaran Kamalaruban Adish Singla Goran Radanović OffRL 93 11 0 09 Feb 2024
How Does Unlabeled Data Provably Help Out-of-Distribution Detection? Xuefeng Du Zhen Fang Ilias Diakonikolas Yixuan Li OODD 87 29 0 05 Feb 2024
Attacking Byzantine Robust Aggregation in High Dimensions Sarthak Choudhary Aashish Kolluri Prateek Saxena AAML 75 1 0 22 Dec 2023
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression Ilias Diakonikolas Daniel M. Kane Ankit Pensia Thanasis Pittas 97 2 0 04 Dec 2023
A Combinatorial Approach to Robust PCA Weihao Kong Mingda Qiao Rajat Sen 48 0 0 28 Nov 2023
Testing with Non-identically Distributed Samples Shivam Garg Chirag Pabbaraju Kirankumar Shiragur Gregory Valiant 55 0 0 19 Nov 2023
Outlier-Robust Wasserstein DRO Sloan Nietert Ziv Goldfeld Soroosh Shafiee 81 11 0 09 Nov 2023
Statistical Barriers to Affine-equivariant Estimation Zihao Chen Yeshwanth Cherapanamjeri 84 0 0 16 Oct 2023
Robust Stochastic Optimization via Gradient Quantile Clipping Ibrahim Merad Stéphane Gaïffas 77 2 0 29 Sep 2023
Byzantine-Resilient Federated PCA and Low Rank Column-wise Sensing Ankit Pratap Singh Namrata Vaswani 94 0 0 25 Sep 2023
$Noisy Computing of the $\mathsf{OR}$ and $\mathsf{MAX}$ Functions$ Noisy Computing of the $\mathsf{OR}$ and $\mathsf{MAX}$ Functions Banghua Zhu Ziao Wang Nadim Ghaddar Jiantao Jiao Lele Wang 61 3 0 07 Sep 2023
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination C. Canonne Samuel B. Hopkins Jungshian Li Allen Liu Shyam Narayanan AAML 75 5 0 18 Jul 2023
The Geometric Median and Applications to Robust Mean Estimation Stanislav Minsker Nate Strawn 64 4 0 06 Jul 2023
Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise Shiwei Zeng Jie Shen 57 1 0 01 Jun 2023
Robust Nonparametric Regression under Poisoning Attack Puning Zhao Z. Wan AAML 80 10 0 26 May 2023
Robust Sparse Mean Estimation via Incremental Learning Jianhao Ma Ruidi Chen Yinghui He Salar Fattahi Wei Hu 67 0 0 24 May 2023
On the Optimal Batch Size for Byzantine-Robust Distributed Learning Yi-Rui Yang Chang-Wei Shi Wu-Jun Li FedML AAML 92 0 0 23 May 2023
Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression Yinan Shen Jingyang Li Jian-Feng Cai Dong Xia 59 1 0 10 May 2023
Learning Mixtures of Gaussians with Censored Data W. Tai Bryon Aragam 41 1 0 06 May 2023
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas OOD 90 10 0 04 May 2023
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm Ilias Diakonikolas D. Kane Jasper C. H. Lee Ankit Pensia Thanasis Pittas 98 1 0 01 May 2023
Robust and differentially private stochastic linear bandits Vasileios Charisopoulos Hossein Esfandiari Vahab Mirrokni FedML 84 1 0 23 Apr 2023
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions Anna P. Meyer Aws Albarghouthi Loris Dántoni 74 15 0 20 Apr 2023
On Private and Robust Bandits Yulian Wu Xingyu Zhou Youming Tao Di Wang 76 7 0 06 Feb 2023
Robust Estimation under the Wasserstein Distance Sloan Nietert Rachel Cummings Ziv Goldfeld 93 5 0 02 Feb 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 73 9 0 30 Jan 2023
Robust empirical risk minimization via Newton's method Eirini Ioannou Muni Sreenivas Pydi Po-Ling Loh 65 2 0 30 Jan 2023
Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians A. Minasyan Nikita Zhivotovskiy 61 9 0 21 Jan 2023
Private estimation algorithms for stochastic block models and mixture models Hongjie Chen Vincent Cohen-Addad Tommaso dÓrsi Alessandro Epasto Jacob Imola David Steurer Stefan Tiegel FedML 95 21 0 11 Jan 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 116 30 0 03 Jan 2023
Privately Estimating a Gaussian: Efficient, Robust and Optimal Daniel Alabi Pravesh Kothari Pranay Tankala Prayaag Venkat Fred Zhang 138 0 0 15 Dec 2022
Corruption-tolerant Algorithms for Generalized Linear Models B. Mukhoty Debojyoti Dey Purushottam Kar 32 1 0 11 Dec 2022
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 113 57 0 09 Dec 2022
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions Ilias Diakonikolas D. Kane Jasper C. H. Lee Ankit Pensia 55 12 0 29 Nov 2022
A Characterization of List Learnability Moses Charikar Chirag Pabbaraju 75 14 0 07 Nov 2022
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation Kristian Georgiev Samuel B. Hopkins FedML 98 24 0 01 Nov 2022
Is Out-of-Distribution Detection Learnable? Zhen Fang Yixuan Li Jie Lu Jiahua Dong Bo Han Feng Liu OODD 137 133 0 26 Oct 2022