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Yuanzhi Li
Yuanzhi Li
Assistant Professor at CMU
E-mail confirmado em andrew.cmu.edu - Página inicial
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Lora: Low-rank adaptation of large language models
EJ Hu, Y Shen, P Wallis, Z Allen-Zhu, Y Li, S Wang, L Wang, W Chen
arXiv preprint arXiv:2106.09685, 2021
55722021
Sparks of artificial general intelligence: Early experiments with gpt-4
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
arXiv preprint arXiv:2303.12712, 2023
25932023
A convergence theory for deep learning via over-parameterization
Z Allen-Zhu, Y Li, Z Song
International conference on machine learning, 242-252, 2019
15422019
Learning and generalization in overparameterized neural networks, going beyond two layers
Z Allen-Zhu, Y Li, Y Liang
Advances in neural information processing systems 32, 2019
8322019
Convergence analysis of two-layer neural networks with relu activation
Y Li, Y Yuan
Advances in neural information processing systems 30, 2017
7442017
Learning overparameterized neural networks via stochastic gradient descent on structured data
Y Li, Y Liang
Advances in neural information processing systems 31, 2018
7042018
A theoretical analysis of NDCG type ranking measures
Y Wang, L Wang, Y Li, D He, TY Liu
Conference on learning theory, 25-54, 2013
6882013
A latent variable model approach to pmi-based word embeddings
S Arora, Y Li, Y Liang, T Ma, A Risteski
Transactions of the Association for Computational Linguistics 4, 385-399, 2016
641*2016
Towards understanding ensemble, knowledge distillation and self-distillation in deep learning
Z Allen-Zhu, Y Li
arXiv preprint arXiv:2012.09816, 2020
3632020
An alternative view: When does SGD escape local minima?
B Kleinberg, Y Li, Y Yuan
International conference on machine learning, 2698-2707, 2018
3452018
Algorithmic regularization in over-parameterized matrix sensing and neural networks with quadratic activations
Y Li, T Ma, H Zhang
Conference On Learning Theory, 2-47, 2018
3372018
Towards explaining the regularization effect of initial large learning rate in training neural networks
Y Li, C Wei, T Ma
Advances in neural information processing systems 32, 2019
3212019
Textbooks are all you need
S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ...
arXiv preprint arXiv:2306.11644, 2023
3022023
Linear algebraic structure of word senses, with applications to polysemy
S Arora, Y Li, Y Liang, T Ma, A Risteski
Transactions of the Association for Computational Linguistics 6, 483-495, 2018
2572018
Algorithmic framework for model-based deep reinforcement learning with theoretical guarantees
Y Luo, H Xu, Y Li, Y Tian, T Darrell, T Ma
arXiv preprint arXiv:1807.03858, 2018
2462018
What can resnet learn efficiently, going beyond kernels?
Z Allen-Zhu, Y Li
Advances in Neural Information Processing Systems 32, 2019
2162019
Gradient descent on neural networks typically occurs at the edge of stability
J Cohen, S Kaur, Y Li, JZ Kolter, A Talwalkar
International Conference on Learning Representations, 2021
2152021
On the convergence rate of training recurrent neural networks
Z Allen-Zhu, Y Li, Z Song
Advances in neural information processing systems 32, 2019
1982019
Textbooks are all you need ii: phi-1.5 technical report
Y Li, S Bubeck, R Eldan, A Del Giorno, S Gunasekar, YT Lee
arXiv preprint arXiv:2309.05463, 2023
1972023
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
S Chen, S Chewi, J Li, Y Li, A Salim, AR Zhang
arXiv preprint arXiv:2209.11215, 2022
1962022
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