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Adaptive Sampling Probabilities for Non-Smooth Optimization.

, , , и . ICML, том 70 из Proceedings of Machine Learning Research, стр. 2574-2583. PMLR, (2017)

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John C Maraldo

John C Angehrn

John C Eisele

Antonio Duchini

Guido C C Clinckspoor

 

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Element Level Differential Privacy: The Right Granularity of Privacy., , и . CoRR, (2019)Lower Bounds for Non-Convex Stochastic Optimization., , , , , и . CoRR, (2019)Minimax rates for memory-bounded sparse linear regression., и . COLT, том 40 из JMLR Workshop and Conference Proceedings, стр. 1564-1587. JMLR.org, (2015)Boosting with structural sparsity., и . ICML, том 382 из ACM International Conference Proceeding Series, стр. 297-304. ACM, (2009)Generalizing to Unseen Domains via Adversarial Data Augmentation., , , , , и . NeurIPS, стр. 5339-5349. (2018)Information-theoretic lower bounds for distributed statistical estimation with communication constraints., , , и . NIPS, стр. 2328-2336. (2013)Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation., , и . NIPS, стр. 1529-1537. (2013)Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems., , , и . NeurIPS, (2020)Minibatch Stochastic Approximate Proximal Point Methods., , , и . NeurIPS, (2020)Accelerated, Optimal and Parallel: Some results on model-based stochastic optimization., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 2811-2827. PMLR, (2022)