Maximilian Lam
Maximilian Lam
Verified email at g.harvard.edu - Homepage
Title
Cited by
Cited by
Year
Speeding up distributed machine learning using codes
K Lee, M Lam, R Pedarsani, D Papailiopoulos, K Ramchandran
IEEE Transactions on Information Theory 64 (3), 1514-1529, 2017
4732017
Gradient diversity: a key ingredient for scalable distributed learning
D Yin, A Pananjady, M Lam, D Papailiopoulos, K Ramchandran, P Bartlett
Proceedings of the 21th International Conference on Artificial Intelligence …, 2017
60*2017
Cyclades: Conflict-free asynchronous machine learning
X Pan, M Lam, S Tu, D Papailiopoulos, C Zhang, MI Jordan, ...
arXiv preprint arXiv:1605.09721, 2016
552016
Cataloging the visible universe through Bayesian inference in Julia at petascale
J Regier, K Fischer, K Pamnany, A Noack, J Revels, M Lam, S Howard, ...
Journal of Parallel and Distributed Computing 127, 89-104, 2019
25*2019
Word2bits-quantized word vectors
M Lam
arXiv preprint arXiv:1803.05651, 2018
192018
Benchmarking TinyML systems: Challenges and direction
CR Banbury, VJ Reddi, M Lam, W Fu, A Fazel, J Holleman, X Huang, ...
arXiv preprint arXiv:2003.04821, 2020
182020
Quantized Reinforcement Learning (QUARL)
S Krishnan, S Chitlangia, M Lam, Z Wan, A Faust, VJ Reddi
arXiv preprint arXiv:1910.01055, 2019
52019
Quantized Neural Network Inference with Precision Batching
M Lam, Z Yedidia, C Banbury, VJ Reddi
arXiv preprint arXiv:2003.00822, 2020
22020
Exploring the Utility of Developer Exhaust
J Zhang, M Lam, S Wang, P Varma, L Nardi, K Olukotun, C Ré
Proceedings of the Second Workshop on Data Management for End-To-End Machine …, 2018
12018
Quantized Reinforcement Learning (QuaRL)
M Lam, S Chitlangia, S Krishnan, Z Wan, G Barth-Maron, A Faust, ...
arXiv e-prints, arXiv: 1910.01055, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–10