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Ziv Goldfeld
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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
1682018
The information bottleneck problem and its applications in machine learning
Z Goldfeld, Y Polyanskiy
IEEE Journal on Selected Areas in Information Theory 1 (1), 19-38, 2020
1362020
Convergence of smoothed empirical measures with applications to entropy estimation
Z Goldfeld, K Greenewald, J Niles-Weed, Y Polyanskiy
arXiv preprint arXiv:1905.13576, 2019
85*2019
Semantic-security capacity for wiretap channels of type II
Z Goldfeld, P Cuff, HH Permuter
IEEE Transactions on Information Theory 62 (7), 3863-3879, 2016
732016
Arbitrarily varying wiretap channels with type constrained states
Z Goldfeld, P Cuff, HH Permuter
IEEE Transactions on Information Theory 62 (12), 7216-7244, 2016
422016
Sliced mutual information: A scalable measure of statistical dependence
Z Goldfeld, K Greenewald
Advances in Neural Information Processing Systems 34, 17567-17578, 2021
412021
Neural estimation of statistical divergences
S Sreekumar, Z Goldfeld
Journal of machine learning research 23 (126), 1-75, 2022
382022
Gaussian-smoothed optimal transport: Metric structure and statistical efficiency
Z Goldfeld, K Greenewald
International Conference on Artificial Intelligence and Statistics, 3327-3337, 2020
372020
Statistical, robustness, and computational guarantees for sliced wasserstein distances
S Nietert, Z Goldfeld, R Sadhu, K Kato
Advances in Neural Information Processing Systems 35, 28179-28193, 2022
352022
Statistical inference with regularized optimal transport
Z Goldfeld, K Kato, G Rioux, R Sadhu
Information and Inference: A Journal of the IMA 13 (1), iaad056, 2024
342024
Wiretap channels with random states non-causally available at the encoder
Z Goldfeld, P Cuff, HH Permuter
IEEE Transactions on Information Theory 66 (3), 1497-1519, 2019
342019
Limit theorems for entropic optimal transport maps and Sinkhorn divergence
Z Goldfeld, K Kato, G Rioux, R Sadhu
Electronic Journal of Statistics 18 (1), 980-1041, 2024
312024
Smooth -Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
S Nietert, Z Goldfeld, K Kato
International Conference on Machine Learning, 8172-8183, 2021
302021
Fourier-Motzkin Elimination Software for Information Theoretic Inequalities
IB Gattegno, Z Goldfeld, HH Permuter
arXiv preprint arXiv:1610.03990, 2016
28*2016
Estimating information flow in neural networks
Z Goldfeld, E van den Berg, K Greenewald, I Melnyk, N Nguyen, ...
arXiv preprint arXiv:1810.05728, 2018
272018
Outlier-robust optimal transport: Duality, structure, and statistical analysis
S Nietert, Z Goldfeld, R Cummings
International Conference on Artificial Intelligence and Statistics, 11691-11719, 2022
262022
Asymptotic guarantees for generative modeling based on the smooth Wasserstein distance
Z Goldfeld, K Greenewald, K Kato
Advances in neural information processing systems 33, 2527-2539, 2020
25*2020
Capacity of continuous channels with memory via directed information neural estimator
Z Aharoni, D Tsur, Z Goldfeld, HH Permuter
2020 IEEE International Symposium on Information Theory (ISIT), 2014-2019, 2020
242020
Neural estimation and optimization of directed information over continuous spaces
D Tsur, Z Aharoni, Z Goldfeld, H Permuter
IEEE Transactions on Information Theory 69 (8), 4777-4798, 2023
212023
Non-asymptotic performance guarantees for neural estimation of f-divergences
S Sreekumar, Z Zhang, Z Goldfeld
International Conference on Artificial Intelligence and Statistics, 3322-3330, 2021
202021
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Artículos 1–20