Maximilian Lam
Maximilian Lam
Verified email at - Homepage
Cited by
Cited by
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
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
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
Cyclades: Conflict-free asynchronous machine learning
X Pan, M Lam, S Tu, D Papailiopoulos, C Zhang, MI Jordan, ...
Advances in Neural Information Processing Systems 29, 2016
Widening access to applied machine learning with tinyml
VJ Reddi, B Plancher, S Kennedy, L Moroney, P Warden, A Agarwal, ...
arXiv preprint arXiv:2106.04008, 2021
The people's speech: A large-scale diverse english speech recognition dataset for commercial usage
D Galvez, G Diamos, J Ciro, JF Cerón, K Achorn, A Gopi, D Kanter, M Lam, ...
arXiv preprint arXiv:2111.09344, 2021
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
Gradient disaggregation: Breaking privacy in federated learning by reconstructing the user participant matrix
M Lam, GY Wei, D Brooks, VJ Reddi, M Mitzenmacher
International Conference on Machine Learning, 5959-5968, 2021
Quantized reinforcement learning (quarl)
S Krishnan, S Chitlangia, M Lam, Z Wan, A Faust, VJ Reddi
arXiv preprint arXiv:1910.01055, 2019
Word2bits-quantized word vectors
M Lam
arXiv preprint arXiv:1803.05651, 2018
GPU-based Private Information Retrieval for On-Device Machine Learning Inference
M Lam, J Johnson, W Xiong, K Maeng, U Gupta, M Rhu, HHS Lee, ...
arXiv preprint arXiv:2301.10904, 2023
Quantized neural network inference with precision batching
M Lam, Z Yedidia, C Banbury, VJ Reddi
arXiv preprint arXiv:2003.00822, 2020
Tabula: Efficiently computing nonlinear activation functions for secure neural network inference
M Lam, M Mitzenmacher, VJ Reddi, GY Wei, D Brooks
arXiv preprint arXiv:2203.02833, 2022
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
The system can't perform the operation now. Try again later.
Articles 1–14