Recent Advances in Algorithmic High-Dimensional Robust Statistics

14 November 2019

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

50 / 71 papers shown

Title
Learning High-dimensional Gaussians from Censored Data Arnab Bhattacharyya C. Daskalakis Themis Gouleakis Yuhao Wang 31 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 67 0 0 01 Apr 2025
Geometric Median (GM) Matching for Robust Data Pruning Anish Acharya Inderjit S Dhillon Sujay Sanghavi AAML 59 0 0 20 Jan 2025
Optimal Rates for Robust Stochastic Convex Optimization Changyu Gao Andrew Lowy Xingyu Zhou Stephen J. Wright 81 0 0 15 Dec 2024
Tolerant Algorithms for Learning with Arbitrary Covariate Shift Surbhi Goel Abhishek Shetty Konstantinos Stavropoulos Arsen Vasilyan OOD 34 2 0 04 Jun 2024
Robust Kernel Hypothesis Testing under Data Corruption Antonin Schrab Ilmun Kim 50 3 0 30 May 2024
Learning from Uncertain Data: From Possible Worlds to Possible Models Jiongli Zhu Su Feng Boris Glavic Babak Salimi 42 0 0 28 May 2024
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 Yi-Rui Yang Chang-Wei Shi Wu-Jun Li FedML AAML 32 0 0 23 May 2023
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
On Private and Robust Bandits Yulian Wu Xingyu Zhou Youming Tao Di Wang 24 5 0 06 Feb 2023
Robust Estimation under the Wasserstein Distance Sloan Nietert Rachel Cummings Ziv Goldfeld 36 4 0 02 Feb 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 41 9 0 30 Jan 2023
Robust empirical risk minimization via Newton's method Eirini Ioannou Muni Sreenivas Pydi Po-Ling Loh 23 2 0 30 Jan 2023
Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians A. Minasyan Nikita Zhivotovskiy 36 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 45 20 0 11 Jan 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 47 28 0 03 Jan 2023
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 23 50 0 09 Dec 2022
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions Ilias Diakonikolas D. Kane Jasper C. H. Lee Ankit Pensia 30 12 0 29 Nov 2022
A Characterization of List Learnability Moses Charikar Chirag Pabbaraju 37 13 0 07 Nov 2022
Is Out-of-Distribution Detection Learnable? Zhen Fang Yixuan Li Jie Lu Jiahua Dong Bo Han Feng Liu OODD 44 125 0 26 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 29 3 0 11 Oct 2022
On Optimal Learning Under Targeted Data Poisoning Steve Hanneke Amin Karbasi Mohammad Mahmoody Idan Mehalel Shay Moran AAML FedML 36 7 0 06 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 37 31 0 30 Sep 2022
Improved covariance estimation: optimal robustness and sub-Gaussian guarantees under heavy tails R. I. Oliveira Zoraida F. Rico 42 10 0 27 Sep 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients Takeyuki Sasai Hironori Fujisawa 35 4 0 24 Aug 2022
Holistic Robust Data-Driven Decisions Amine Bennouna Bart P. G. Van Parys Ryan Lucas OOD 41 22 0 19 Jul 2022
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates Takeyuki Sasai 26 4 0 15 Jun 2022
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models Pranjal Awasthi Abhimanyu Das Weihao Kong Rajat Sen 25 6 0 09 Jun 2022
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models Ilias Diakonikolas D. Kane Yuxin Sun 33 1 0 09 Jun 2022
Certifying Data-Bias Robustness in Linear Regression Anna P. Meyer Aws Albarghouthi Loris Dántoni 35 3 0 07 Jun 2022
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 Yiding Chen Xuezhou Zhang Kaipeng Zhang Mengdi Wang Xiaojin Zhu OffRL 29 16 0 01 Jun 2022
Communication-efficient distributed eigenspace estimation with arbitrary node failures Vasileios Charisopoulos Anil Damle 16 1 0 31 May 2022
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 40 25 0 17 May 2022
Robust Testing in High-Dimensional Sparse Models Anand George C. Canonne 48 3 0 16 May 2022
Streaming Algorithms for High-Dimensional Robust Statistics Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas 24 21 0 26 Apr 2022
Robust estimation algorithms don't need to know the corruption level Ayush Jain A. Orlitsky V. Ravindrakumar 21 6 0 11 Feb 2022
Robust Voting Rules from Algorithmic Robust Statistics Allen Liu Ankur Moitra 26 4 0 13 Dec 2021
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 38 46 0 07 Dec 2021
Clustering Mixtures with Almost Optimal Separation in Polynomial Time Jingkai Li Allen Liu 30 23 0 01 Dec 2021
Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination Arpan Mukherjee A. Tajer Pin-Yu Chen Payel Das AAML FedML 34 9 0 14 Nov 2021
Robust Estimation for Random Graphs Jayadev Acharya Ayush Jain Gautam Kamath A. Suresh Huanyu Zhang 35 8 0 09 Nov 2021
Certifying Robustness to Programmable Data Bias in Decision Trees Anna P. Meyer Aws Albarghouthi Loris Dántoni 27 21 0 08 Oct 2021
Outlier-Robust Sparse Estimation via Non-Convex Optimization Yu Cheng Ilias Diakonikolas Rong Ge Shivam Gupta D. Kane Mahdi Soltanolkotabi 52 13 0 23 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 43 16 0 20 Sep 2021
ReLU Regression with Massart Noise Ilias Diakonikolas Jongho Park Christos Tzamos 56 11 0 10 Sep 2021
Robust Regression Revisited: Acceleration and Improved Estimation Rates A. Jambulapati Jingkai Li T. Schramm Kevin Tian AAML 32 17 0 22 Jun 2021
Non-asymptotic analysis and inference for an outlyingness induced winsorized mean Y. Zuo 27 1 0 05 May 2021
Learning GMMs with Nearly Optimal Robustness Guarantees Allen Liu Ankur Moitra 26 15 0 19 Apr 2021