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Kristjan Greenewald
Kristjan Greenewald
Research Scientist, MIT-IBM Watson AI Lab, IBM Research
Geverifieerd e-mailadres voor ibm.com - Homepage
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The computational limits of deep learning
NC Thompson, K Greenewald, K Lee, GF Manso
arXiv preprint arXiv:2007.05558, 2020
4732020
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
4612019
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
1552018
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
1232020
Deep learning's diminishing returns: The cost of improvement is becoming unsustainable
NC Thompson, K Greenewald, K Lee, GF Manso
ieee Spectrum 58 (10), 50-55, 2021
852021
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
65*2020
Action centered contextual bandits
K Greenewald, A Tewari, S Murphy, P Klasnja
Advances in neural information processing systems 30, 2017
532017
The computational limits of deep learning. arXiv 2020
NC Thompson, K Greenewald, K Lee, GF Manso
arXiv preprint arXiv:2007.05558, 2007
462007
Robust kronecker product PCA for spatio-temporal covariance estimation
K Greenewald, AO Hero
IEEE Transactions on Signal Processing 63 (23), 6368-6378, 2015
392015
Tensor graphical lasso (TeraLasso)
K Greenewald, S Zhou, A Hero III
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2019
382019
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
332016
Sample efficient active learning of causal trees
K Greenewald, D Katz, K Shanmugam, S Magliacane, M Kocaoglu, ...
Advances in Neural Information Processing Systems 32, 2019
302019
Statistical model aggregation via parameter matching
M Yurochkin, M Agarwal, S Ghosh, K Greenewald, N Hoang
Advances in neural information processing systems 32, 2019
292019
Kronecker sum decompositions of space-time data
K Greenewald, T Tsiligkaridis, AO Hero
2013 5th IEEE International Workshop on Computational Advances in Multi …, 2013
282013
Gaussian-smoothed optimal transport: Metric structure and statistical efficiency
Z Goldfeld, K Greenewald
International Conference on Artificial Intelligence and Statistics, 3327-3337, 2020
252020
Active structure learning of causal DAGs via directed clique trees
C Squires, S Magliacane, K Greenewald, D Katz, M Kocaoglu, ...
Advances in Neural Information Processing Systems 33, 21500-21511, 2020
252020
Ensemble estimation of information divergence
KR Moon, K Sricharan, K Greenewald, AO Hero III
Entropy 20 (8), 560, 2018
232018
Robust SAR STAP via Kronecker decomposition
K Greenewald, E Zelnio, AH Hero
IEEE Transactions on Aerospace and Electronic Systems 52 (6), 2612-2625, 2016
222016
Sliced mutual information: A scalable measure of statistical dependence
Z Goldfeld, K Greenewald
Advances in Neural Information Processing Systems 34, 17567-17578, 2021
212021
Nonparametric ensemble estimation of distributional functionals
KR Moon, K Sricharan, K Greenewald, AO Hero
arXiv preprint arXiv:1601.06884, 2016
212016
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Artikelen 1–20