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2020 – today
- 2024
[c9]Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová:
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity. ICLR 2024- [c8]Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro:
Asymptotics of feature learning in two-layer networks after one gradient-step. ICML 2024 - [c7]Dominik Schröder, Daniil Dmitriev, Hugo Cui, Bruno Loureiro:
Asymptotics of Learning with Deep Structured (Random) Features. ICML 2024 - [i12]Hugo Cui, Freya Behrens, Florent Krzakala, Lenka Zdeborová:
A phase transition between positional and semantic learning in a solvable model of dot-product attention. CoRR abs/2402.03902 (2024) - [i11]Hugo Cui, Luca Pesce
, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro:
Asymptotics of feature learning in two-layer networks after one gradient-step. CoRR abs/2402.04980 (2024) - [i10]Dominik Schröder, Daniil Dmitriev, Hugo Cui, Bruno Loureiro:
Asymptotics of Learning with Deep Structured (Random) Features. CoRR abs/2402.13999 (2024) - [i9]Hugo Cui:
High-dimensional learning of narrow neural networks. CoRR abs/2409.13904 (2024) - 2023
- [j2]Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Error scaling laws for kernel classification under source and capacity conditions. Mach. Learn. Sci. Technol. 4(3): 35033 (2023) - [c6]Hugo Cui, Florent Krzakala, Lenka Zdeborová:
Bayes-optimal Learning of Deep Random Networks of Extensive-width. ICML 2023: 6468-6521 - [c5]Dominik Schröder, Hugo Cui, Daniil Dmitriev, Bruno Loureiro:
Deterministic equivalent and error universality of deep random features learning. ICML 2023: 30285-30320 - [c4]Hugo Cui, Lenka Zdeborová:
High-dimensional Asymptotics of Denoising Autoencoders. NeurIPS 2023 - [i8]Hugo Cui, Florent Krzakala, Lenka Zdeborová:
Optimal Learning of Deep Random Networks of Extensive-width. CoRR abs/2302.00375 (2023) - [i7]Dominik Schröder, Hugo Cui, Daniil Dmitriev, Bruno Loureiro:
Deterministic equivalent and error universality of deep random features learning. CoRR abs/2302.00401 (2023) - [i6]Hugo Cui, Lenka Zdeborová:
High-dimensional Asymptotics of Denoising Autoencoders. CoRR abs/2305.11041 (2023) - [i5]Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová:
Analysis of learning a flow-based generative model from limited sample complexity. CoRR abs/2310.03575 (2023) - 2022
- [i4]Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Error Rates for Kernel Classification under Source and Capacity Conditions. CoRR abs/2201.12655 (2022) - 2021
- [j1]Hugo Cui, Luca Saglietti, Lenka Zdeborová:
Large deviations in the perceptron model and consequences for active learning. Mach. Learn. Sci. Technol. 2(4): 45001 (2021) - [c3]Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. NeurIPS 2021: 10131-10143 - [c2]Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Learning curves of generic features maps for realistic datasets with a teacher-student model. NeurIPS 2021: 18137-18151 - [i3]Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model. CoRR abs/2102.08127 (2021) - [i2]Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. CoRR abs/2105.15004 (2021) - 2020
- [c1]Hugo Cui, Luca Saglietti, Lenka Zdeborová:
Large deviations for the perceptron model and consequences for active learning. MSML 2020: 390-430
2010 – 2019
- 2019
- [i1]Hugo Cui, Luca Saglietti, Lenka Zdeborová:
Large deviations for the perceptron model and consequences for active learning. CoRR abs/1912.03927 (2019)
Coauthor Index
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