Learning from Untrusted Data

7 November 2016

Papers citing "Learning from Untrusted Data"

50 / 186 papers shown

Title
Learning High-dimensional Gaussians from Censored Data Arnab Bhattacharyya C. Daskalakis Themis Gouleakis Yuhao Wang 31 0 0 28 Apr 2025
Computing High-dimensional Confidence Sets for Arbitrary Distributions Chao Gao Liren Shan Vaidehi Srinivas Aravindan Vijayaraghavan 50 0 0 03 Apr 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination Ilias Diakonikolas Giannis Iakovidis D. Kane Thanasis Pittas 84 0 0 20 Feb 2025
Entangled Mean Estimation in High-Dimensions Ilias Diakonikolas D. Kane Sihan Liu Thanasis Pittas 43 1 0 10 Jan 2025
Adaptive and oblivious statistical adversaries are equivalent Guy Blanc Gregory Valiant AAML 25 0 0 17 Oct 2024
LiD-FL: Towards List-Decodable Federated Learning Hong Liu Liren Shan Han Bao Ronghui You Yuhao Yi Jiancheng Lv FedML 49 0 0 09 Aug 2024
Robust Mixture Learning when Outliers Overwhelm Small Groups Daniil Dmitriev Rares-Darius Buhai Stefan Tiegel Alexander Wolters Gleb Novikov Amartya Sanyal David Steurer Fanny Yang 52 1 0 22 Jul 2024
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks Lukas Gosch Mahalakshmi Sabanayagam D. Ghoshdastidar Stephan Günnemann AAML 45 3 0 15 Jul 2024
On the Relevance of Byzantine Robust Optimization Against Data Poisoning Sadegh Farhadkhani R. Guerraoui Nirupam Gupta Rafael Pinot AAML 41 1 0 01 May 2024
Teach LLMs to Phish: Stealing Private Information from Language Models Ashwinee Panda Christopher A. Choquette-Choo Zhengming Zhang Yaoqing Yang Prateek Mittal PILM 40 20 0 01 Mar 2024
Multi-Model 3D Registration: Finding Multiple Moving Objects in Cluttered Point Clouds David Jin Sushrut Karmalkar Harry Zhang Luca Carlone 3DPC 40 12 0 16 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 31 16 0 02 Feb 2024
Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation Ilias Diakonikolas Daniel M. Kane Jasper C. H. Lee Thanasis Pittas 32 1 0 19 Dec 2023
Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances Spencer Compton Gregory Valiant 25 2 0 05 Dec 2023
A Combinatorial Approach to Robust PCA Weihao Kong Mingda Qiao Rajat Sen 11 0 0 28 Nov 2023
Pseudo-label Correction for Instance-dependent Noise Using Teacher-student Framework Eugene Kim NoLa 33 0 0 24 Nov 2023
Testing with Non-identically Distributed Samples Shivam Garg Chirag Pabbaraju Kirankumar Shiragur Gregory Valiant 24 0 0 19 Nov 2023
Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities Subash Neupane Shaswata Mitra Ivan A. Fernandez Swayamjit Saha Sudip Mittal Jingdao Chen Nisha Pillai Shahram Rahimi 29 12 0 12 Oct 2023
Early Warning Prediction with Automatic Labeling in Epilepsy Patients Peng Zhang Ting Gao Jinqiu Guo Jinqiao Duan Sergey Nikolenko 29 1 0 09 Oct 2023
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption Shubhada Agrawal Timothée Mathieu D. Basu Odalric-Ambrym Maillard 30 2 0 28 Sep 2023
Linear Regression using Heterogeneous Data Batches Ayush Jain Rajat Sen Weihao Kong Abhimanyu Das A. Orlitsky 28 3 0 05 Sep 2023
Private Distribution Learning with Public Data: The View from Sample Compression Shai Ben-David Alex Bie C. Canonne Gautam Kamath Vikrant Singhal 49 11 0 11 Aug 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers Puning Zhao Zhiguo Wan OOD FedML 45 4 0 25 Jul 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 38 1 0 01 May 2023
Data-Driven Subgroup Identification for Linear Regression Zachary Izzo Ruishan Liu James Zou OOD 23 4 0 29 Apr 2023
A Generative Framework for Low-Cost Result Validation of Machine Learning-as-a-Service Inference Abhinav Kumar Miguel A. Guirao Aguilera R. Tourani Satyajayant Misra AAML 32 0 0 31 Mar 2023
Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal Error He Jia Pravesh Kothari Santosh Vempala 21 2 0 23 Feb 2023
Robust Mean Estimation Without Moments for Symmetric Distributions Gleb Novikov David Steurer Stefan Tiegel OOD 31 0 0 21 Feb 2023
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity Youssef Allouah Sadegh Farhadkhani R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 45 50 0 03 Feb 2023
Imbalanced Mixed Linear Regression Pini Zilber B. Nadler 21 5 0 29 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 43 20 0 11 Jan 2023
Efficient List-Decodable Regression using Batches Abhimanyu Das Ayush Jain Weihao Kong Rajat Sen 28 4 0 23 Nov 2022
A Characterization of List Learnability Moses Charikar Chirag Pabbaraju 37 13 0 07 Nov 2022
Learning from a Biased Sample Roshni Sahoo Lihua Lei Stefan Wager 27 17 0 05 Sep 2022
Estimation Contracts for Outlier-Robust Geometric Perception Luca Carlone 38 22 0 22 Aug 2022
How many labelers do you have? A closer look at gold-standard labels Chen Cheng Hilal Asi John C. Duchi 23 6 0 24 Jun 2022
List-Decodable Covariance Estimation Misha Ivkov Pravesh Kothari 24 7 0 22 Jun 2022
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering Ilias Diakonikolas D. Kane Sushrut Karmalkar Ankit Pensia Thanasis Pittas 22 13 0 10 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
List-Decodable Sparse Mean Estimation Shiwei Zeng Jie Shen 27 9 0 28 May 2022
Byzantine Machine Learning Made Easy by Resilient Averaging of Momentums Sadegh Farhadkhani R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 36 67 0 24 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 31 7 0 05 May 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 51 109 0 31 Mar 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 Linear Regression for General Feature Distribution Tom Norman Nir Weinberger Kfir Y. Levy OOD 22 2 0 04 Feb 2022
Robust supervised learning with coordinate gradient descent Stéphane Gaïffas Ibrahim Merad OOD 33 2 0 31 Jan 2022
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection Seong Min Kye Kwanghee Choi Joonyoung Yi Buru Chang NoLa 35 15 0 29 Nov 2021
On the power of adaptivity in statistical adversaries Guy Blanc Jane Lange Ali Malik Li-Yang Tan AAML 20 8 0 19 Nov 2021
Conditional Linear Regression for Heterogeneous Covariances Brendan Juba Leda Liang 24 0 0 15 Nov 2021
Kalman Filtering with Adversarial Corruptions Sitan Chen Frederic Koehler Ankur Moitra Morris Yau AAML 27 10 0 11 Nov 2021