受强制性开放获取政策约束的文章 - Mijung Park了解详情
可在其他位置公开访问的文章：5 篇
DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation
F Harder, K Adamczewski, M Park
International Conference on Artificial Intelligence and Statistics, 1819-1827, 2021
强制性开放获取政策： Federal Ministry of Education and Research, Germany
DP-EM: Differentially Private Expectation Maximization
M Park, J Foulds, K Chaudhuri, M Welling
AISTATS 2017, 2017
强制性开放获取政策： US National Science Foundation
Dethroning the Fano Factor: a flexible, model-based approach to partitioning neural variability
AS Charles, M Park, JP Weller, GD Horwitz, JW Pillow
Neural computation 30 (4), 1012-1045, 2018
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Sparse Bayesian structure learning with “dependent relevance determination” priors
A Wu, M Park, OO Koyejo, JW Pillow
Advances in Neural Information Processing Systems, 1628-1636, 2014
强制性开放获取政策： US National Institutes of Health
Dirichlet Pruning for Convolutional Neural Networks
K Adamczewski, M Park
International Conference on Artificial Intelligence and Statistics, 3637-3645, 2021
强制性开放获取政策： Federal Ministry of Education and Research, Germany
出版信息和资助信息由计算机程序自动确定