Kristjan Greenewald
Kristjan Greenewald
Research Staff Member, IBM Research AI
Verified email at - Homepage
Cited by
Cited by
Bayesian nonparametric federated learning of neural networks
M Yurochkin, M Agarwal, S Ghosh, K Greenewald, N Hoang, Y Khazaeni
International Conference on Machine Learning, 7252-7261, 2019
Estimating information flow in deep neural networks
Z Goldfeld, E Berg, K Greenewald, I Melnyk, N Nguyen, B Kingsbury, ...
arXiv preprint arXiv:1810.05728, 2018
The computational limits of deep learning
NC Thompson, K Greenewald, K Lee, GF Manso
arXiv preprint arXiv:2007.05558, 2020
Action centered contextual bandits
K Greenewald, A Tewari, P Klasnja, S Murphy
Advances in neural information processing systems 30, 5973, 2017
Improving convergence of divergence functional ensemble estimators
KR Moon, K Sricharan, K Greenewald, AO Hero
2016 IEEE International Symposium on Information Theory (ISIT), 1133-1137, 2016
Robust kronecker product PCA for spatio-temporal covariance estimation
K Greenewald, AO Hero
IEEE Transactions on Signal Processing 63 (23), 6368-6378, 2015
Kronecker sum decompositions of space-time data
K Greenewald, T Tsiligkaridis, AO Hero
2013 5th IEEE International Workshop on Computational Advances in Multi …, 2013
Nonparametric ensemble estimation of distributional functionals
KR Moon, K Sricharan, K Greenewald, AO Hero
arXiv preprint arXiv:1601.06884, 2016
Personalized heartsteps: A reinforcement learning algorithm for optimizing physical activity
P Liao, K Greenewald, P Klasnja, S Murphy
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2020
Convergence of smoothed empirical measures with applications to entropy estimation
Z Goldfeld, K Greenewald, J Niles-Weed, Y Polyanskiy
IEEE Transactions on Information Theory 66 (7), 4368-4391, 2020
Ensemble estimation of information divergence
KR Moon, K Sricharan, K Greenewald, AO Hero
Entropy 20 (8), 560, 2018
Regularized block toeplitz covariance matrix estimation via kronecker product expansions
K Greenewald, AO Hero
2014 IEEE Workshop on Statistical Signal Processing (SSP), 9-12, 2014
Gaussian-smoothed optimal transport: Metric structure and statistical efficiency
Z Goldfeld, K Greenewald
International Conference on Artificial Intelligence and Statistics, 3327-3337, 2020
Robust SAR STAP via Kronecker decomposition
K Greenewald, E Zelnio, AH Hero
IEEE Transactions on Aerospace and Electronic Systems 52 (6), 2612-2625, 2016
Tensor graphical lasso (TeraLasso)
K Greenewald, S Zhou, A Hero III
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2019
Estimating differential entropy under Gaussian convolutions
Z Goldfeld, K Greenewald, Y Polyanskiy
arXiv preprint arXiv:1810.11589, 2018
Optimality of the plug-in estimator for differential entropy estimation under Gaussian convolutions
Z Goldfeld, K Greenewald, J Weed, Y Polyanskiy
2019 IEEE International Symposium on Information Theory (ISIT), 892-896, 2019
Time-dependent spatially varying graphical models, with application to brain fMRI data analysis
K Greenewald, S Park, S Zhou, A Giessing
arXiv preprint arXiv:1711.03701, 2017
Asymptotic guarantees for generative modeling based on the smooth wasserstein distance
Z Goldfeld, K Greenewald, K Kato
Advances in neural information processing systems, 2020
Statistical model aggregation via parameter matching
M Yurochkin, M Agarwal, S Ghosh, K Greenewald, TN Hoang
arXiv preprint arXiv:1911.00218, 2019
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