Követés
Yi Zhang
Yi Zhang
Senior Researcher at Microsoft Research Redmond
E-mail megerősítve itt: microsoft.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Sparks of artificial general intelligence: Early experiments with gpt-4
S Bubeck, V Chadrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
ArXiv, 2023
38822023
Phi-3 technical report: A highly capable language model locally on your phone
M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ...
arXiv preprint arXiv:2404.14219, 2024
9472024
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
S Arora, R Ge, Y Liang, T Ma, Y Zhang
arXiv preprint arXiv:1703.00573, 2017
8512017
Stronger generalization bounds for deep nets via a compression approach
S Arora, R Ge, B Neyshabur, Y Zhang
International conference on machine learning, 254-263, 2018
7252018
Textbooks are all you need
S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ...
arXiv preprint arXiv:2306.11644, 2023
5842023
Convolutional neural networks with low-rank regularization
C Tai, T Xiao, Y Zhang, X Wang
arXiv preprint arXiv:1511.06067, 2015
5692015
Deep visual analogy-making
SE Reed, Y Zhang, Y Zhang, H Lee
Advances in neural information processing systems 28, 2015
3802015
Phi-2: The surprising power of small language models
M Javaheripi, S Bubeck, M Abdin, J Aneja, S Bubeck, CCT Mendes, ...
Microsoft Research Blog 1 (3), 3, 2023
2252023
Do GANs actually learn the distribution? An empirical study
S Arora, Y Zhang
arXiv:1706.08224, 2017
2072017
Do GANs learn the distribution? some theory and empirics
S Arora, A Risteski, Y Zhang
International conference on learning representations, 2018
1882018
Spectral filtering for general linear dynamical systems
E Hazan, H Lee, K Singh, C Zhang, Y Zhang
Advances in Neural Information Processing Systems 31, 2018
1142018
What makes convolutional models great on long sequence modeling?
Y Li, T Cai, Y Zhang, D Chen, D Dey
arXiv preprint arXiv:2210.09298, 2022
1092022
Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets
R Kuditipudi, X Wang, H Lee, Y Zhang, Z Li, W Hu, S Arora, R Ge
arXiv:1906.06247, 2019
1002019
Towards Understanding the Invertibility of Convolutional Neural Networks
CA Gilbert, Y Zhang, K Lee, Y Zhang, H Lee
arXiv preprint arXiv:1705.08664, 2017
812017
Unveiling transformers with lego: a synthetic reasoning task
Y Zhang, A Backurs, S Bubeck, R Eldan, S Gunasekar, T Wagner
arXiv preprint arXiv:2206.04301, 2022
752022
Efficient full-matrix adaptive regularization
N Agarwal, B Bullins, X Chen, E Hazan, K Singh, C Zhang, Y Zhang
International Conference on Machine Learning, 102-110, 2019
702019
Why are convolutional nets more sample-efficient than fully-connected nets?
Z Li, Y Zhang, S Arora
arXiv preprint arXiv:2010.08515, 2020
612020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
Y Zhang, O Plevrakis, SS Du, X Li, Z Song, S Arora
arXiv:2002.06668, 2020
542020
Phi-4 technical report
M Abdin, J Aneja, H Behl, S Bubeck, R Eldan, S Gunasekar, M Harrison, ...
arXiv preprint arXiv:2412.08905, 2024
532024
Learning threshold neurons via the "edge of stability"
K Ahn, S Bubeck, S Chewi, YT Lee, F Suarez, Y Zhang
arxiv.org/2212.07469, 2022
462022
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Cikkek 1–20