{"list":"other","total":54,"rows":[{"id":"2107.06917","title":"A Field Guide to Federated Optimization","created":"2021-07-14","cited_by_count":315},{"id":"1706.03691","title":"Certified Defenses for Data Poisoning Attacks","created":"2017-06-09","cited_by_count":303},{"id":"1604.06443","title":"Robust Estimators in High Dimensions without the Computational Intractability","created":"2016-04-21","cited_by_count":209},{"id":"1604.06968","title":"Agnostic Estimation of Mean and Covariance","created":"2016-04-24","cited_by_count":131},{"id":"1803.02815","title":"Sever: A Robust Meta-Algorithm for Stochastic Optimization","created":"2018-03-07","cited_by_count":125},{"id":"1611.02315","title":"Learning from Untrusted Data","created":"2016-11-07","cited_by_count":90},{"id":"1703.00893","title":"Being Robust (in High Dimensions) Can Be Practical","created":"2017-03-02","cited_by_count":83},{"id":"1711.07454","title":"Mixture Models, Robustness, and Sum of Squares Proofs","created":"2017-11-20","cited_by_count":81},{"id":"1802.06485","title":"Robust Estimation via Robust Gradient Estimation","created":"2018-02-19","cited_by_count":76},{"id":"1806.00040","title":"Efficient Algorithms and Lower Bounds for Robust Linear Regression","created":"2018-05-31","cited_by_count":76},{"id":"1803.03241","title":"Efficient Algorithms for Outlier-Robust Regression","created":"2018-03-08","cited_by_count":72},{"id":"1711.07211","title":"List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians","created":"2017-11-20","cited_by_count":70},{"id":"2009.12976","title":"Robust regression with covariate filtering: Heavy tails and adversarial contamination","created":"2020-09-27","cited_by_count":50},{"id":"2002.08936","title":"Meta-learning for mixed linear regression","created":"2020-02-20","cited_by_count":44},{"id":"2007.15839","title":"Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization","created":"2020-07-31","cited_by_count":44},{"id":"1905.05679","title":"List-Decodable Linear Regression","created":"2019-05-14","cited_by_count":42},{"id":"1906.11366","title":"Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection","created":"2019-06-26","cited_by_count":41},{"id":"2006.09702","title":"Robust Meta-learning for Mixed Linear Regression with Small Batches","created":"2020-06-17","cited_by_count":41},{"id":"1506.02428","title":"Robust Regression via Hard Thresholding","created":"2015-06-08","cited_by_count":39},{"id":"1704.03866","title":"Robustly Learning a Gaussian: Getting Optimal Error, Efficiently","created":"2017-04-12","cited_by_count":39},{"id":"1802.07895","title":"Learning Mixtures of Linear Regressions with Nearly Optimal Complexity","created":"2018-02-22","cited_by_count":37},{"id":"1905.04660","title":"List Decodable Learning via Sum of Squares","created":"2019-05-12","cited_by_count":37},{"id":"2006.06980","title":"Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing","created":"2020-06-12","cited_by_count":35},{"id":"1809.07425","title":"Mean Estimation with Sub-Gaussian Rates in Polynomial Time","created":"2018-09-19","cited_by_count":33},{"id":"2007.08137","title":"Optimal Robust Linear Regression in Nearly Linear Time","created":"2020-07-16","cited_by_count":32},{"id":"1904.06288","title":"Outlier-robust estimation of a sparse linear model using $\\ell_1$-penalized Huber's $M$-estimator","created":"2019-04-12","cited_by_count":31},{"id":"1805.11643","title":"High Dimensional Robust Sparse Regression","created":"2018-05-29","cited_by_count":29},{"id":"1906.04661","title":"Faster Algorithms for High-Dimensional Robust Covariance Estimation","created":"2019-06-11","cited_by_count":28},{"id":"2005.06417","title":"Robustly Learning any Clusterable Mixture of Gaussians","created":"2020-05-13","cited_by_count":28},{"id":"2012.07774","title":"Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models","created":"2020-12-14","cited_by_count":28},{"id":"1608.05749","title":"Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization","created":"2016-08-19","cited_by_count":26},{"id":"1912.07629","title":"Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments","created":"2019-12-16","cited_by_count":26},{"id":"2106.09689","title":"Statistical Query Lower Bounds for List-Decodable Linear Regression","created":"2021-06-17","cited_by_count":25},{"id":"1903.08192","title":"Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression","created":"2019-03-19","cited_by_count":23},{"id":"1306.3729","title":"Spectral Experts for Estimating Mixtures of Linear Regressions","created":"2013-06-17","cited_by_count":22},{"id":"1702.04656","title":"Robust Regression via Mutivariate Regression Depth","created":"2017-02-15","cited_by_count":20},{"id":"2005.09796","title":"List Decodable Mean Estimation in Nearly Linear Time","created":"2020-05-20","cited_by_count":20},{"id":"2006.10715","title":"List-Decodable Mean Estimation via Iterative Multi-Filtering","created":"2020-06-18","cited_by_count":18},{"id":"2011.09973","title":"List-Decodable Mean Estimation in Nearly-PCA Time","created":"2020-11-19","cited_by_count":17},{"id":"1606.05374","title":"Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction","created":"2016-06-16","cited_by_count":15},{"id":"2006.14211","title":"Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems","created":"2020-06-25","cited_by_count":15},{"id":"2106.11938","title":"Robust Regression Revisited: Acceleration and Improved Estimation Rates","created":"2021-06-22","cited_by_count":15},{"id":"2201.11211","title":"Learning Mixtures of Linear Dynamical Systems","created":"2022-01-26","cited_by_count":15},{"id":"1711.08113","title":"Learning Discrete Distributions from Untrusted Batches","created":"2017-11-22","cited_by_count":14},{"id":"2002.10384","title":"On the Sample Complexity of Adversarial Multi-Source PAC Learning","created":"2020-02-24","cited_by_count":11},{"id":"1911.08532","title":"Optimal Robust Learning of Discrete Distributions from Batches","created":"2019-11-19","cited_by_count":10},{"id":"2205.13166","title":"On Learning Mixture of Linear Regressions in the Non-Realizable Setting","created":"2022-05-26","cited_by_count":10},{"id":"2006.13312","title":"Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time","created":"2020-06-23","cited_by_count":9},{"id":"2002.10435","title":"Learning Structured Distributions From Untrusted Batches: Faster and Simpler","created":"2020-02-24","cited_by_count":8},{"id":"2002.11099","title":"A General Method for Robust Learning from Batches","created":"2020-02-25","cited_by_count":8},{"id":"2111.05320","title":"Robust Estimation for Random Graphs","created":"2021-11-09","cited_by_count":8},{"id":"1809.08055","title":"Compressed Sensing with Adversarial Sparse Noise via L1 Regression","created":"2018-09-21","cited_by_count":7},{"id":"2206.04777","title":"Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models","created":"2022-06-09","cited_by_count":6},{"id":"1911.11838","title":"Robustly Clustering a Mixture of Gaussians","created":"2019-11-26","cited_by_count":2}],"next_cursor":null}