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Distributed Learning

123 directly classified papers

Papers per year

Papers

A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning CVPR 2024
An Empirical Study of Distributed Deep Learning Training on Edge (Student Abstract) AAAI 2024
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation AAAI 2023
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems AAAI 2023
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning AAAI 2023
DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training CVPR 2023
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting NIPS 2023
$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning NIPS 2023
Robust and Actively Secure Serverless Collaborative Learning NIPS 2023
Buffered Asynchronous SGD for Byzantine Learning JMLR 2023
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction NIPS 2023
DynaFed: Tackling Client Data Heterogeneity With Global Dynamics CVPR 2023
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022
Distributed Learning with Strategic Users: A Repeated Game Approach AAAI 2022
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning NIPS 2022
A Unified Analysis of Federated Learning with Arbitrary Client Participation NIPS 2022
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels NIPS 2022
Coordinate Linear Variance Reduction for Generalized Linear Programming NIPS 2022
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing NIPS 2022
Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space NIPS 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression NIPS 2022
Acceleration in Distributed Sparse Regression NIPS 2022
Communication-efficient SGD: From Local SGD to One-Shot Averaging NIPS 2021
P3: Distributed Deep Graph Learning at Scale OSDI 2021
Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains (Demo) AAAI 2021