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Issue (2021:Dec.)

2. A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent*This article is an updated version of: Liao Z, Couillet R and Mahoney M W 2020 A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent Advances in Neural Information Processing Systems vol 33, ed H Larochelle, M Ranzato, R Hadsell, M F Balcan and H Lin (New York: Curran Associates), pp 13939–50. (29th December 2021)

Authors:
Liao, Zhenyu; Couillet, Romain; Mahoney, Michael W
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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3. Active learning of continuous-time Bayesian networks through interventions*This article is an updated version of: Linzner D and Koeppl H 2021 Active learning of continuous-time Bayesian networks through interventions Proc. 38th Int. Conf. on Machine Learning vol 139 ed M Meila and T Zhang pp 6692–701. (29th December 2021)

Authors:
Linzner, Dominik; Koeppl, Heinz
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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4. An analytic theory of shallow networks dynamics for hinge loss classification*This article is an updated version of: Pellegrini F and Biroli G 2020 An analytic theory of shallow networks dynamics for hinge loss classification Advances in Neural Information Processing Systems vol 33 ed H Larochelle, M Ranzato, R Hadsell, M F Balcan and H Lin (New York: Curran Associates) pp 5356–67. (29th December 2021)

Authors:
Pellegrini, Franco; Biroli, Giulio
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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5. Augmenting physical models with deep networks for complex dynamics forecasting*This article is an updated version of: Yin Y, Le Guen V, Dona J, de Bezenac E, Ayed I, Thome N and Gallinari P 2021 Augmenting physical models with deep networks for complex dynamics forecasting Int. Conf. Learning Representations. (29th December 2021)

Authors:
Yin, Yuan; Le Guen, Vincent; Dona, Jérémie; de Bézenac, Emmanuel; Ayed, Ibrahim; Thome, Nicolas; Gallinari, Patrick
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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7. Deep double descent: where bigger models and more data hurt*This article is an updated version of: Nakkiran P, Kaplun G, Bansal Y, Yang T, Barak B and Sutskever I 2020 Deep double descent: where bigger models and more data hurt Int. Conf. Learning Representations. (29th December 2021)

Authors:
Nakkiran, Preetum; Kaplun, Gal; Bansal, Yamini; Yang, Tristan; Barak, Boaz; Sutskever, Ilya
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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9. Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification*This article is an updated version of: Mignacco F, Krzakala F, Urbani P and Zdeborová L 2020 Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification Advances in Neural Information Processing Systems vol 33 ed H Larochelle, M Ranzato, R Hadsell, M F Balcan and H Lin (New York: Curran Associates) pp 9540–50. (29th December 2021)

Authors:
Mignacco, Francesca; Krzakala, Florent; Urbani, Pierfrancesco; Zdeborová, Lenka
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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10. Efficient learning of discrete graphical models*This article is an updated version of: Vuffray M, Misra S and Lokhov A 2020 Efficient Learning of Discrete Graphical Models Advances in Neural Information Processing Systems vol 33 eds H Larochelle, M Ranzato, R Hadsell, M F Balcan and H Lin (New York: Curran Associates) pp 13575–85. (7th January 2022)

Authors:
Vuffray, Marc; Misra, Sidhant; Lokhov, Andrey Y
Journal:
Journal of statistical mechanics
Issue:
(2021:Dec.)
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