Virginia Smith
Cited by
Cited by
Federated multi-task learning
V Smith, CK Chiang, M Sanjabi, AS Talwalkar
Advances in neural information processing systems, 4424-4434, 2017
Federated learning: Challenges, methods, and future directions
T Li, AK Sahu, A Talwalkar, V Smith
IEEE Signal Processing Magazine 37 (3), 50-60, 2020
Communication-efficient distributed dual coordinate ascent
M Jaggi*, V Smith*, M Takác, J Terhorst, S Krishnan, T Hofmann, ...
Advances in Neural Information Processing Systems, 3068-3076, 2014
Federated optimization in heterogeneous networks
T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smith
arXiv preprint arXiv:1812.06127, 2018
MLI: An API for distributed machine learning
ER Sparks, A Talwalkar, V Smith, J Kottalam, X Pan, J Gonzalez, ...
2013 IEEE 13th International Conference on Data Mining, 1187-1192, 2013
Adding vs. averaging in distributed primal-dual optimization
C Ma*, V Smith*, M Jaggi, MI Jordan, P Richtárik, ...
International Conference on Machine Learning, 2015
Leaf: A benchmark for federated settings
S Caldas, SMK Duddu, P Wu, T Li, J Konečný, HB McMahan, V Smith, ...
arXiv preprint arXiv:1812.01097, 2018
CoCoA: A general framework for communication-efficient distributed optimization
V Smith, S Forte, C Ma, M Takáč, MI Jordan, M Jaggi
The Journal of Machine Learning Research 18 (1), 8590-8638, 2017
Distributed optimization with arbitrary local solvers
C Ma, J Konečný, M Jaggi, V Smith, MI Jordan, P Richtárik, M Takáč
Optimization Methods and Software 32 (4), 813-848, 2017
Identifying models of HVAC systems using semiparametric regression
A Aswani, N Master, J Taneja, V Smith, A Krioukov, D Culler, C Tomlin
2012 American Control Conference (ACC), 3675-3680, 2012
Fair resource allocation in federated learning
T Li, M Sanjabi, A Beirami, V Smith
arXiv preprint arXiv:1905.10497, 2019
A kernel theory of modern data augmentation
T Dao, A Gu, AJ Ratner, V Smith, C De Sa, C Ré
Proceedings of machine learning research 97, 1528, 2019
One-shot federated learning
N Guha, A Talwalkar, V Smith
arXiv preprint arXiv:1902.11175, 2019
Mlbase: A distributed machine learning wrapper
A Talwalkar, T Kraska, R Griffith, J Duchi, J Gonzalez, D Britz, X Pan, ...
NIPS Big Learning Workshop, 35, 2012
L1-regularized distributed optimization: A communication-efficient primal-dual framework
V Smith, S Forte, MI Jordan, M Jaggi
arXiv preprint arXiv:1512.04011, 2015
Modeling building thermal response to HVAC zoning
V Smith, T Sookoor, K Whitehouse
ACM SIGBED Review 9 (3), 39-45, 2012
Feddane: A federated newton-type method
T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smithy
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1227-1231, 2019
A comparative study of high renewables penetration electricity grids
J Taneja, V Smith, D Culler, C Rosenberg
2013 IEEE International Conference on Smart Grid Communications …, 2013
SysML: The New Frontier of Machine Learning Systems.
A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ...
Efficient augmentation via data subsampling
M Kuchnik, V Smith
arXiv preprint arXiv:1810.05222, 2018
The system can't perform the operation now. Try again later.
Articles 1–20