[CTBJ22] Y. Cherapanamjeri, N. Tripuraneni, P. L. Bartlett, and M. I. Jordan. "Optimal Mean Estimation without a Variance". In: Proc. 35th Annual Conference on Learning Theory (COLT). 2022.
[Dep20] J. Depersin. "A Spectral Algorithm for Robust Regression with Subgaussian Rates". In: CoRR abs/2007.06072 (2020).
[DHL19] Y. Dong, S. B. Hopkins, and J. Li. "Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection". In: Advances in Neural Information Processing Systems 32 (NeurIPS). 2019.
[DK19] I. Diakonikolas and D. M. Kane. "Recent Advances in Algorithmic High-Dimensional Robust Statistics". In: CoRR abs/1911.05911 (2019).
[DK23] I. Diakonikolas and D. M. Kane. Algorithmic High-Dimensional Robust Statistics. https://sites.google.com/view/ars-book/. Cambridge University Press, 2023.
[DKKLMS16] I. Diakonikolas, G. Kamath, D. M. Kane, J. Li, A. Moitra, and A. Stewart. "Robust Estimators in High Dimensions without the Computational Intractability". In: Proc. 57th IEEE Symposium on Foundations of Computer Science (FOCS). 2016, pp. 655-664.
[DKKLMS17] I. Diakonikolas, G. Kamath, D. M. Kane, J. Li, A. Moitra, and A. Stewart. “Being Robust (in High Dimensions) Can Be Practical”. In: Proceedings of the 34th International Conference on Machine Learning, ICML 2017. 2017, pp. 999–1008.
[DKKLMS18] I. Diakonikolas, G. Kamath, D. M. Kane, J. Li, A. Moitra, and A. Stewart. "Robustly Learning a Gaussian: Getting Optimal Error, Efficiently". In: Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018. Full version available at https://arxiv.org/abs/1704.03866. 2018, pp. 2683-2702.
[DKKLSS19] I. Diakonikolas, G. Kamath, D. Kane, J. Li, J. Steinhardt, and A. Stewart. "Sever: A Robust Meta-Algorithm for Stochastic Optimization". In: Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 2019, pp. 1596–1606.
[DKKLT21] I. Diakonikolas, D. M. Kane, D. Kongsgaard, J. Li, and K. Tian. "List-decodable mean estimation in nearly-pca time". In: Advances in Neural Information Processing Systems 34 (NeurIPS). Vol. 34. 2021.
[DKKLT22] I. Diakonikolas, D. M. Kane, D. Kongsgaard, J. Li, and K. Tian. "Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation". In: Proc. 54th Annual ACM Symposium on Theory of Computing (STOC). 2022.
[DKKPP22] I. Diakonikolas, D. M. Kane, S. Karmalkar, A. Pensia, and T. Pittas. "Robust Sparse Mean Estimation via Sum of Squares". In: Proc. 35th Annual Conference on Learning Theory (COLT). 2022.
[DKKPS19] I. Diakonikolas, D. M. Kane, S. Karmalkar, E. Price, and A. Stewart. "Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering". In: Advances in Neural Information Processing Systems 32 (NeurIPS). 2019.
[DKLP22] I. Diakonikolas, D. M. Kane, J. C. H. Lee, and A. Pensia. "Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions". In: Advances in Neural Information Processing Systems 35 (NeurIPS). 2022.
[DKP20] I. Diakonikolas, D. M. Kane, and A. Pensia. "Outlier Robust Mean Estimation with Subgaussian Rates via Stability". In: Advances in Neural Information Processing Systems 33 (NeurIPS). 2020.
[DKPP22] I. Diakonikolas, D. M. Kane, A. Pensia, and T. Pittas. "Streaming algorithms for high-dimensional robust statistics". In: International Conference on Machine Learning. PMLR. 2022, pp. 5061-5117.
[DKPP23] I. Diakonikolas, D. M. Kane, A. Pensia, and T. Pittas. "Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA". In: Proc. 40th International Conference on Machine Learning (ICML). 2023.
[DKS17] I. Diakonikolas, D. M. Kane, and A. Stewart. "Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures". In: 58th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2017. Full version at http://arxiv.org/abs/1611.03473. 2017, pp. 73-84.