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Orthogonal Machine Learning: Power and Limitations.

, , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5723-5731. PMLR, (2018)

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Orthogonal Machine Learning: Power and Limitations., , and . CoRR, (2017)Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm, and . (2017)cite arxiv:1711.04952.Mixed-Integer Convex Representability., , and . IPCO, volume 10328 of Lecture Notes in Computer Science, page 392-404. Springer, (2017)The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics., , , , , and . NeurIPS, (2022)Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena., , , and . CoRR, (2020)Self-Regularity of Output Weights for Overparameterized Two-Layer Neural Networks., , and . ISIT, page 819-824. IEEE, (2021)Optimal Private Median Estimation under Minimal Distributional Assumptions., , and . NeurIPS, (2020)Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions., , and . NeurIPS, (2022)Stationary Points of Shallow Neural Networks with Quadratic Activation Function., , and . CoRR, (2019)Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks., , and . IEEE Trans. Signal Process., (2022)