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Beidi Chen
Beidi Chen
E-mail confirmado em andrew.cmu.edu
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FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU
Y Sheng, L Zheng, B Yuan, Z Li, M Ryabinin, B Chen, P Liang, C Re, ...
International Conference on Machine Learning, 2023
1762023
Efficient streaming language models with attention sinks
G Xiao, Y Tian, B Chen, S Han, M Lewis
arXiv preprint arXiv:2309.17453, 2023
1602023
SLIDE: In Defense of Smart Algorithms over Hardware Acceleration for Large-scale Deep Learning Systems
B Chen, T Medini, J Farwell, S Gobriel, C Tai, A Shrivastava
Proceedings of Machine Learning and System 2, 291--306, 2020
1282020
Deja vu: Contextual sparsity for efficient llms at inference time
Z Liu, J Wang, T Dao, T Zhou, B Yuan, Z Song, A Shrivastava, C Zhang, ...
International Conference on Machine Learning, 22137-22176, 2023
1182023
Scatterbrain: Unifying sparse and low-rank attention
B Chen, T Dao, E Winsor, Z Song, A Rudra, C Ré
Advances in Neural Information Processing Systems 34, 17413-17426, 2021
982021
H O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Z Zhang, Y Sheng, T Zhou, T Chen, L Zheng, R Cai, Z Song, Y Tian, C Ré, ...
International Conference on Machine Learning, 2023
882023
MONGOOSE: A learnable LSH framework for efficient neural network training
B Chen, Z Liu, B Peng, Z Xu, JL Li, T Dao, Z Song, A Shrivastava, C Re
International Conference on Learning Representations, 2021
712021
Monarch: Expressive structured matrices for efficient and accurate training
T Dao, B Chen, NS Sohoni, A Desai, M Poli, J Grogan, A Liu, A Rao, ...
International Conference on Machine Learning, 4690-4721, 2022
702022
Analyzing log analysis: An empirical study of user log mining
S Alspaugh, B Chen, J Lin, A Ganapathi, M Hearst, R Katz
28th Large Installation System Administration Conference (LISA14), 62-77, 2014
682014
Pixelated butterfly: Simple and efficient sparse training for neural network models
B Chen, T Dao, K Liang, J Yang, Z Song, A Rudra, C Re
International Conference on Learning Representations, 2022
65*2022
Decentralized training of foundation models in heterogeneous environments
B Yuan, Y He, JQ Davis, T Zhang, T Dao, B Chen, P Liang, C Re, C Zhang
Neural Information Processing Systems., 2022
602022
Angular visual hardness
B Chen, W Liu, Z Yu, J Kautz, A Shrivastava, A Garg, A Anandkumar
International Conference on Machine Learning, 1637-1648, 2020
512020
Fast and accurate stochastic gradient estimation
B Chen, Y Xu, A Shrivastava
Advances in Neural Information Processing Systems 32, 2019
48*2019
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer
Y Tian, Y Wang, B Chen, S Du
International Conference on Machine Learning, 2023
462023
Unique entity estimation with application to the Syrian conflict
B Chen, A Shrivastava, RC Steorts
The Annals of Applied Statistics 12 (2), 1039-1067, 2018
362018
Sub-linear privacy-preserving near-neighbor search
MS Riazi, B Chen, A Shrivastava, D Wallach, F Koushanfar
arXiv preprint arXiv:1612.01835, 2016
25*2016
Densified winner take all (WTA) hashing for sparse datasets
B Chen, A Shrivastava
Uncertainty in artificial intelligence, 2018
23*2018
Joma: Demystifying multilayer transformers via joint dynamics of mlp and attention
Y Tian, Y Wang, Z Zhang, B Chen, S Du
arXiv preprint arXiv:2310.00535, 2023
212023
Cocktailsgd: Fine-tuning foundation models over 500mbps networks
J Wang, Y Lu, B Yuan, B Chen, P Liang, C De Sa, C Re, C Zhang
International Conference on Machine Learning, 36058-36076, 2023
192023
Compress, then prompt: Improving accuracy-efficiency trade-off of llm inference with transferable prompt
Z Xu, Z Liu, B Chen, Y Tang, J Wang, K Zhou, X Hu, A Shrivastava
arXiv preprint arXiv:2305.11186, 2023
182023
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