Obserwuj
Jian Zhang
Jian Zhang
CTO & VP of Engineering, Nexusflow.ai
Brak zweryfikowanego adresu e-mail - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Squad: 100,000+ questions for machine comprehension of text
P Rajpurkar, J Zhang, K Lopyrev, P Liang
Conference on Empirical Methods in Natural Language Processing, 2016
93092016
DAWNBench: An End-to-End Deep Learning Benchmark and Competition
C Coleman, D Narayanan, D Kang, T Zhao, J Zhang, L Nardi, P Bailis, ...
SysML conference, 2018
3992018
Analysis of the Time-To-Accuracy Metric and Entries in the DAWNBench Deep Learning Benchmark
C Coleman, D Kang, D Narayanan, L Nardi, T Zhao, J Zhang, P Bailis, ...
Workshop on Systems for ML and Open Source Software at NeurIPS 2018, 2018
148*2018
Pipemare: Asynchronous pipeline parallel dnn training
B Yang, J Zhang, J Li, C Ré, C Aberger, C De Sa
Proceedings of Machine Learning and Systems 3, 269-296, 2021
1382021
High-accuracy low-precision training
C De Sa, M Leszczynski, J Zhang, A Marzoev, CR Aberger, K Olukotun, ...
arXiv preprint arXiv:1803.03383, 2018
1352018
Parallel SGD: When does averaging help?
J Zhang, C De Sa, I Mitliagkas, C Ré
arXiv preprint arXiv:1606.07365, 2016
1302016
YellowFin and the Art of Momentum Tuning
J Zhang, I Mitliagkas
SysML Conference, 2019
1182019
Low-memory neural network training: A technical report
NS Sohoni, CR Aberger, M Leszczynski, J Zhang, C Ré
arXiv preprint arXiv:1904.10631, 2019
1172019
Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors
J Zhang, K Chen, A Schwing, R Urtasun
International Conference on Computer Vision, 2013
1072013
Deep learning at 15pf: supervised and semi-supervised classification for scientific data
T Kurth, J Zhang, N Satish, E Racah, I Mitliagkas, MMA Patwary, T Malas, ...
Proceedings of the International Conference for High Performance Computing …, 2017
972017
Contextual embeddings: When are they worth it?
S Arora, A May, J Zhang, C Ré
arXiv preprint arXiv:2005.09117, 2020
932020
On the tool manipulation capability of open-source large language models
Q Xu, F Hong, B Li, C Hu, Z Chen, J Zhang
arXiv preprint arXiv:2305.16504, 2023
892023
Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation
J Zhang, A May, T Dao, C Ré
International Conference on Artificial Intelligence and Statistics, 2018
402018
On the downstream performance of compressed word embeddings
A May, J Zhang, T Dao, C Ré
Advances in neural information processing systems 32, 2019
282019
Revisiting BFfloat16 Training
P Zamirai, J Zhang, CR Aberger, C De Sa
242020
Higher-Order Inference for Multi-class Log-supermodular Models
J Zhang, J Djolonga, A Krause
International Conference on Computer Vision, 2015
222015
Training with Low-precision Embedding Tables
J Zhang, J Yang, H Yuen
202018
Understanding the downstream instability of word embeddings
M Leszczynski, A May, J Zhang, S Wu, C Aberger, C Ré
Proceedings of Machine Learning and Systems 2, 262-290, 2020
182020
Message Passing Inference for Large Scale Graphical Models with High Order Potentials
J Zhang, A Schwing, U Raquel
Advances in Neural Information Processing Systems, 2015
82015
Athene-70b: Redefining the boundaries of post-training for open models, July 2024
E Frick, P Jin, T Li, K Ganesan, J Zhang, J Jiao, B Zhu
URL https://huggingface. co/Nexusflow/Athene-70B, 2024
2*2024
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