Obserwuj
Sai Praneeth Karimireddy
Sai Praneeth Karimireddy
Inne imiona/nazwiskaSai Praneeth Reddy Karimireddy, Sai Praneeth Reddy
USC
Zweryfikowany adres z usc.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
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
36112019
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
5972019
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
4162021
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
377*2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
T Vogels, SP Karimireddy, M Jaggi
NeurIPS 2019 - Conference on Neural Information Processing Systems, 2019
3732019
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
332*2020
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
314*2019
Learning from History for Byzantine Robust Optimization
SP Karimireddy, L He, M Jaggi
ICML 2021 - International Conference on Machine Learning, 2020
2182020
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
SP Karimireddy*, L He*, M Jaggi
ICLR 2022 - International Conference on Learning Representations, 2021
189*2021
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
JO Terrail, SS Ayed, E Cyffers, F Grimberg, C He, R Loeb, P Mangold, ...
NeurIPS 2022 - Conference on Neural Information Processing Systems, 2022
141*2022
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
1102021
Agree to Disagree: Diversity through Disagreement for Better Transferability
M Pagliardini, M Jaggi, F Fleuret, SP Karimireddy
ICLR 2023 - International Conference on Learning Representations, 2022
812022
Secure Byzantine-Robust Machine Learning
L He, SP Karimireddy, M Jaggi
NeurIPS workshop on Federated Learning (FL-NeurIPS), 2020
762020
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
692021
Towards Model Agnostic Federated Learning Using Knowledge Distillation
A Afonin, SP Karimireddy
ICLR 2022 - International Conference on Learning Representations, 2021
672021
Mechanisms that Incentivize Data Sharing in Federated Learning
SP Karimireddy, W Guo, MI Jordan
Workshop on Federated Learning: Recent Advances and New Challenges (in …, 2022
612022
Byzantine-Robust Decentralized Learning via Self-Centered Clipping
L He, SP Karimireddy, M Jaggi
ICML Workshop on Federated learning (FL-ICML), 2022
61*2022
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
58*2020
Accelerating Gradient Boosting Machine
H Lu*, SP Karimireddy*, N Ponomareva, V Mirrokni
AISTATS 2020 - International Conference on Artificial Intelligence and …, 2019
522019
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
492018
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20