Suivre
Sai Praneeth Karimireddy
Sai Praneeth Karimireddy
Postdoc, UC Berkeley
Adresse e-mail validée de berkeley.edu - Page d'accueil
Titre
Citée par
Citée par
Année
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
SP Karimireddy, S Kale, M Mohri, SJ Reddi, SU Stich, AT Suresh
ICML 2020 - International Conference on Machine Learning, 2019
660*2019
Error Feedback Fixes SignSGD and other Gradient Compression Schemes
SP Karimireddy, Q Rebjock, SU Stich, M Jaggi
ICML 2019 - International Conference on Machine Learning, 2019
2892019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
T Vogels, SP Karimireddy, M Jaggi
NeurIPS 2019 - Conference on Neural Information Processing Systems, 2019
1432019
The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication
SU Stich, SP Karimireddy
JMLR 2020 - Journal of Machine Learning Research, 2019
135*2019
Why are adaptive methods good for attention models?
J Zhang, SP Karimireddy, A Veit, S Kim, SJ Reddi, S Kumar, S Sra
NeurIPS 2020 - Conference on Neural Information Processing Systems, 2019
104*2019
A Field Guide to Federated Optimization
J Wang*, Z Charles*, Z Xu*, G Joshi*, HB McMahan, M Al-Shedivat, ...
arXiv preprint arXiv:2107.06917, 2021
962021
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
SP Karimireddy, M Jaggi, S Kale, M Mohri, SJ Reddi, SU Stich, AT Suresh
NeurIPS 2021 - Conference on Neural Information Processing Systems, 2020
682020
Learning from History for Byzantine Robust Optimization
SP Karimireddy, L He, M Jaggi
ICML 2021 - International Conference on Machine Learning, 2020
432020
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
SP Karimireddy*, L He*, M Jaggi
ICLR 2022 - International Conference on Learning Representations, 2021
27*2021
Assignment techniques for crowdsourcing sensitive tasks
LE Celis, SP Reddy, IP Singh, S Vaya
Proceedings of the 19th ACM Conference on Computer-Supported Cooperative …, 2016
262016
Secure Byzantine-Robust Machine Learning
L He, SP Karimireddy, M Jaggi
arXiv preprint arXiv:2006.04747, 2020
252020
Global linear convergence of Newton's method without strong-convexity or Lipschitz gradients
SP Karimireddy, SU Stich, M Jaggi
NeurIPS 2019 Workshop 'Beyond First Order Methods in ML', 2018
252018
Accelerating Gradient Boosting Machine
H Lu*, SP Karimireddy*, N Ponomareva, V Mirrokni
AISTATS 2020 - International Conference on Artificial Intelligence and …, 2019
232019
Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
T Lin, SP Karimireddy, SU Stich, M Jaggi
ICML 2021 - International Conference on Machine Learning, 2021
222021
On Matching Pursuit and Coordinate Descent
F Locatello, A Raj, SP Karimireddy, G Rätsch, B Schölkopf, SU Stich, ...
ICML 2018 - Proceedings of the 35th International Conference on Machine Learning, 2018
212018
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning
T Vogels, SP Karimireddy, M Jaggi
NeurIPS 2020 - Conference on Neural Information Processing Systems, 2020
20*2020
Efficient Greedy Coordinate Descent for Composite Problems
SP Karimireddy*, A Koloskova*, SU Stich, M Jaggi
AISTATS 2019 - International Conference on Artificial Intelligence and …, 2018
182018
RelaySum for Decentralized Deep Learning on Heterogeneous Data
T Vogels*, L He*, A Koloskova, T Lin, SP Karimireddy, SU Stich, M Jaggi
NeurIPS 2021 - Conference on Neural Information Processing Systems, 2021
142021
Multi-Broadcasting under the SINR Model
SP Karimireddy, DR Kowalski, S Vaya
PODC 2016 - Proceedings of the 2016 ACM Symposium on Principles of …, 2016
13*2016
Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems
SP Karimireddy, S Stich, M Jaggi
AISTATS 2018 - International Conference on Artificial Intelligence and …, 2018
112018
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–20