Folgen
Hugo Cui
Hugo Cui
Postdoctoral fellow, Harvard CMSA
Bestätigte E-Mail-Adresse bei fas.harvard.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Learning curves of generic features maps for realistic datasets with a teacher-student model
B Loureiro, C Gerbelot, H Cui, S Goldt, F Krzakala, M Mezard, ...
Advances in Neural Information Processing Systems 34, 18137-18151, 2021
195*2021
Generalization error rates in kernel regression: The crossover from the noiseless to noisy regime
H Cui, B Loureiro, F Krzakala, L Zdeborová
Advances in Neural Information Processing Systems 34, 10131-10143, 2021
982021
Bayes-optimal learning of deep random networks of extensive-width
H Cui, F Krzakala, L Zdeborová
International Conference on Machine Learning 40, 6468-6521, 2023
402023
Deterministic equivalent and error universality of deep random features learning
D Schröder, H Cui, D Dmitriev, B Loureiro
International Conference on Machine Learning, 30285-30320, 2023
352023
Error scaling laws for kernel classification under source and capacity conditions
H Cui, B Loureiro, F Krzakala, L Zdeborová
Machine Learning: Science and Technology 4 (3), 035033, 2023
22*2023
Asymptotics of feature learning in two-layer networks after one gradient-step
H Cui, L Pesce, Y Dandi, F Krzakala, YM Lu, L Zdeborová, B Loureiro
arXiv preprint arXiv:2402.04980, 2024
202024
Analysis of learning a flow-based generative model from limited sample complexity
H Cui, F Krzakala, E Vanden-Eijnden, L Zdeborová
arXiv preprint arXiv:2310.03575, 2023
202023
High-dimensional asymptotics of denoising autoencoders
H Cui, L Zdeborová
Advances in Neural Information Processing Systems 36, 11850-11890, 2023
162023
Large deviations for the perceptron model and consequences for active learning
H Cui, L Saglietti, L Zdeborova
Mathematical and Scientific Machine Learning, 390-430, 2020
122020
A phase transition between positional and semantic learning in a solvable model of dot-product attention
H Cui, F Behrens, F Krzakala, L Zdeborová
arXiv preprint arXiv:2402.03902, 2024
112024
Asymptotics of Learning with Deep Structured (Random) Features
D Schröder, D Dmitriev, H Cui, B Loureiro
arXiv preprint arXiv:2402.13999, 2024
92024
A random matrix theory perspective on the spectrum of learned features and asymptotic generalization capabilities
Y Dandi, L Pesce, H Cui, F Krzakala, YM Lu, B Loureiro
arXiv preprint arXiv:2410.18938, 2024
22024
A precise asymptotic analysis of learning diffusion models: theory and insights
H Cui, C Pehlevan, YM Lu
arXiv preprint arXiv:2501.03937, 2025
12025
High-dimensional learning of narrow neural networks
H Cui
arXiv preprint arXiv:2409.13904, 2024
12024
Topics in statistical physics of high-dimensional machine learning
HC Cui
EPFL, 2024
12024
Large deviations of semisupervised learning in the stochastic block model
H Cui, L Saglietti, L Zdeborová
Physical Review E 105 (3), 034108, 2022
12022
Fundamental limits of learning in sequence multi-index models and deep attention networks: High-dimensional asymptotics and sharp thresholds
E Troiani, H Cui, Y Dandi, F Krzakala, L Zdeborová
arXiv preprint arXiv:2502.00901, 2025
2025
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–17