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Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels.

, , , and . J. Mach. Learn. Res., (2020)

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Inferring high-dimensional poisson autoregressive models., , and . SSP, page 1-5. IEEE, (2016)Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming., , and . J. Mach. Learn. Res., (2012)Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness., , and . NIPS, page 1563-1570. Curran Associates, Inc., (2009)Estimating Network Structure from Incomplete Event Data., , and . CoRR, (2018)Network estimation via poisson autoregressive models., , and . CAMSAP, page 1-5. IEEE, (2017)Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits., , , and . J. Mach. Learn. Res., (2022)Enhanced Blocking Probability Evaluation Method for Circuit-Switched Trunk Reservation Networks., , , and . IEEE Communications Letters, 11 (6): 543-545 (2007)Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model., and . CoRR, (2021)Minimax rates of convergence for high-dimensional regression under ℓq-ball sparsity., , and . Allerton, page 251-257. IEEE, (2009)Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes., , , and . NeurIPS, (2020)