Vladimir Braverman
机构: Victor E. Cameron Professor of Computer Science, Rice University
主页: rice.edu
每年引用次数
引用次数
引用: 4,788
H-指数: 34
I10-指数 : 82
出版物: 188
Zero-one frequency laws
Vladimir Braverman , Rafail Ostrovsky
Proceedings of the 42nd ACM symposium on Theory of computing - STOC '10 281 -290
61
2010
Pretrained models for multilingual federated learning
Orion Weller , Marc Marone , Vladimir Braverman , Dawn Lawrie
arXiv preprint arXiv:2206.02291
3
2022
Adversarial robustness of streaming algorithms through importance sampling
Vladimir Braverman , Avinatan Hassidim , Yossi Matias , Mariano Schain
Advances in Neural Information Processing Systems 34 3544 -3557
18
2021
Sublinear time spectral density estimation
Vladimir Braverman , Aditya Krishnan , Christopher Musco
Smpte Journal 1144 -1157
5
2022
From Local to Global: Spectral-Inspired Graph Neural Networks
Ningyuan Huang , Soledad Villar , Carey E Priebe , Da Zheng
arXiv preprint arXiv:2209.12054
2022
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging
Guangyao Zheng , Michael A Jacobs , Vladimir Braverman , Vishwa S Parekh
arXiv preprint arXiv:2303.06783
2023
Sparsity and heterogeneous dropout for continual learning in the null space of neural activations
Ali Abbasi , Parsa Nooralinejad , Vladimir Braverman , Hamed Pirsiavash
Smpte Journal 617 -628
5
2022
The benefits of implicit regularization from sgd in least squares problems
Difan Zou , Jingfeng Wu , Vladimir Braverman , Quanquan Gu
Advances in neural information processing systems 34 5456 -5468
15
2021
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
Zirui Liu , Jiayi Yuan , Hongye Jin , Shaochen Zhong
arXiv preprint arXiv:2402.02750
8
2024
Benign Overfitting of Constant-Stepsize SGD for Linear Regression
Difan Zou , Jingfeng Wu , Vladimir Braverman , Quanquan Gu
COLT
58
2021
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu , Difan Zou , Vladimir Braverman , Quanquan Gu
International Conference on Learning Representations
32
2021
Last iterate risk bounds of sgd with decaying stepsize for overparameterized linear regression
Jingfeng Wu , Difan Zou , Vladimir Braverman , Quanquan Gu
International Conference on Machine Learning 24280 -24314
23
2022
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
Jingfeng Wu , Difan Zou , Zixiang Chen , Vladimir Braverman
arXiv preprint arXiv:2310.08391
17
2023
The power and limitation of pretraining-finetuning for linear regression under covariate shift
Jingfeng Wu , Difan Zou , Vladimir Braverman , Quanquan Gu
Advances in Neural Information Processing Systems 35 33041 -33053
12
2022
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron
Jingfeng Wu , Difan Zou , Zixiang Chen , Vladimir Braverman
International Conference on Machine Learning
6
2023
Risk bounds of multi-pass sgd for least squares in the interpolation regime
Difan Zou , Jingfeng Wu , Vladimir Braverman , Quanquan Gu
Advances in Neural Information Processing Systems 35 12909 -12920
4
2022
2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)| 978-1-6654-5519-0/22/$31.00© 2022 IEEE| DOI: 10.1109/FOCS54457. 2022.00116
Amir Abboud , Xavier Allamigeon , Nima Anari , Michael Anastos
Method and system for creation and dynamic updating of best data arrangement in digital data store system
Yossi Matias , Guy Shaked , Vladimir Braverman , Victor Belyaev
6
2013
Provable data subset selection for efficient neural networks training
Murad Tukan , Samson Zhou , Alaa Maalouf , Daniela Rus
International Conference on Machine Learning 34533 -34555
5
2023