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Monte Carlo Gradient Estimation in Machine Learning

, , , and . (2019)cite arxiv:1906.10652Comment: 59 pages, under review.

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Training Language GANs from Scratch., , , and . NeurIPS, page 4302-4313. (2019)Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective., , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 3734-3744. PMLR, (2021)Monte Carlo Gradient Estimation in Machine Learning, , , and . (2019)cite arxiv:1906.10652Comment: 59 pages, under review.A case for new neural network smoothness constraints., , , and . ICBINB@NeurIPS, volume 137 of Proceedings of Machine Learning Research, page 21-32. PMLR, (2020)Discretization Drift in Two-Player Games., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 9064-9074. PMLR, (2021)Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step., , , , , and . ICLR (Poster), OpenReview.net, (2018)On a continuous time model of gradient descent dynamics and instability in deep learning., , , and . CoRR, (2023)Why neural networks find simple solutions: The many regularizers of geometric complexity., , , and . NeurIPS, (2022)Monte Carlo Gradient Estimation in Machine Learning., , , and . J. Mach. Learn. Res., (2020)Deep Compressed Sensing., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 6850-6860. PMLR, (2019)