| Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs | 0 | 0.34 | 2022 |
| Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation | 0 | 0.34 | 2022 |
| Aligning AI With Shared Human Values | 0 | 0.34 | 2021 |
| Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. | 0 | 0.34 | 2021 |
| List-Decodable Mean Estimation in Nearly-PCA Time. | 0 | 0.34 | 2021 |
| Byzantine-Resilient Non-Convex Stochastic Gradient Descent | 0 | 0.34 | 2021 |
| Robustness meets algorithms | 0 | 0.34 | 2021 |
| Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time | 0 | 0.34 | 2020 |
| Efficiently Learning Structured Distributions from Untrusted Batches | 0 | 0.34 | 2020 |
| Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent | 1 | 0.35 | 2020 |
| Entanglement is Necessary for Optimal Quantum Property Testing | 0 | 0.34 | 2020 |
| Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing | 0 | 0.34 | 2020 |
| Randomized Smoothing of All Shapes and Sizes | 0 | 0.34 | 2020 |
| Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization | 0 | 0.34 | 2020 |
| Learning Structured Distributions From Untrusted Batches: Faster and Simpler | 0 | 0.34 | 2020 |
| Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments | 0 | 0.34 | 2020 |
| How Hard Is Robust Mean Estimation? | 0 | 0.34 | 2019 |
| Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers | 2 | 0.35 | 2019 |
| Sample Efficient Toeplitz Covariance Estimation. | 0 | 0.34 | 2019 |
| Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. | 0 | 0.34 | 2019 |
| Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection. | 0 | 0.34 | 2019 |
| Robust Estimators in High-Dimensions Without the Computational Intractability | 1 | 0.36 | 2019 |
| On Mean Estimation for General Norms with Statistical Queries. | 0 | 0.34 | 2019 |
| Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. | 7 | 0.46 | 2018 |
| Byzantine Stochastic Gradient Descent. | 9 | 0.58 | 2018 |
| Privately Learning High-Dimensional Distributions. | 1 | 0.37 | 2018 |
| Spectral Signatures in Backdoor Attacks. | 7 | 0.44 | 2018 |
| Distributionally Linearizable Data Structures. | 1 | 0.35 | 2018 |
| On the Limitations of First-Order Approximation in GAN Dynamics. | 1 | 0.35 | 2018 |
| Sever: A Robust Meta-Algorithm for Stochastic Optimization. | 10 | 0.53 | 2018 |
| Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. | 3 | 0.41 | 2018 |
| Being Robust (in High Dimensions) Can Be Practical. | 16 | 0.67 | 2017 |
| QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. | 27 | 0.77 | 2017 |
| Computationally Efficient Robust Sparse Estimation in High Dimensions. | 4 | 0.42 | 2017 |
| The Power of Choice in Priority Scheduling. | 3 | 0.38 | 2017 |
| Robust Sparse Estimation Tasks in High Dimensions. | 8 | 0.57 | 2017 |
| Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities. | 3 | 0.41 | 2017 |
| Exact Model Counting of Query Expressions: Limitations of Propositional Methods. | 4 | 0.39 | 2017 |
| Mixture models, robustness, and sum of squares proofs | 9 | 0.54 | 2017 |
| ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning. | 9 | 0.68 | 2017 |
| Communication-Efficient Distributed Learning of Discrete Distributions. | 1 | 0.35 | 2017 |
| Towards Understanding the Dynamics of Generative Adversarial Networks. | 11 | 0.73 | 2017 |
| QSGD: Randomized Quantization for Communication-Optimal Stochastic Gradient Descent. | 11 | 0.68 | 2016 |
| Fast Algorithms for Segmented Regression. | 2 | 0.36 | 2016 |
| Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms | 12 | 0.62 | 2015 |
| Sample-Optimal Density Estimation in Nearly-Linear Time | 21 | 0.90 | 2015 |
| The SprayList: a scalable relaxed priority queue | 33 | 1.10 | 2015 |
| On The Importance Of Registers For Computability | 0 | 0.34 | 2014 |
| Replacing Mark Bits with Randomness in Fibonacci Heaps. | 0 | 0.34 | 2014 |
| Model Counting of Query Expressions: Limitations of Propositional Methods. | 3 | 0.38 | 2013 |
