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Distributed Learning
123 directly classified papers
Papers per year
2006: 1
2007: 1
2008: 1
2009: 1
2010: 1
2011: 1
2012: 4
2013: 6
2014: 6
2015: 4
2016: 4
2017: 7
2018: 6
2019: 11
2020: 7
2021: 15
2022: 10
2023: 10
2024: 16
2025: 11
Papers
EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity
AAAI 2025
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness
AAAI 2025
Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning
AAAI 2025
DCHM: Dynamic Collaboration of Heterogeneous Models Through Isomerism Learning in a Blockchain-Powered Federated Learning Framework
AAAI 2025
Scalable Decentralized Algorithms for Online Personalized Mean Estimation
AAAI 2025
ZEN: Empowering Distributed Training with Sparsity-driven Data Synchronization
OSDI 2025
WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling
AAAI 2025
Capture Global Feature Statistics for One-Shot Federated Learning
AAAI 2025
FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors
CVPR 2025
Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology
AAAI 2025
Distributed Cascaded Manifold Hashing Network for Compact Image Set Representation
IJCAI 2025
JointSQ: Joint Sparsification-Quantization for Distributed Learning
CVPR 2024
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models
NIPS 2024
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning
CVPR 2024
Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models
NIPS 2024
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD
NIPS 2024
An Empirical Study of Distributed Deep Learning Training on Edge (Student Abstract)
AAAI 2024
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
NIPS 2024
SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
NIPS 2024
Communication Efficient Distributed Newton Method over Unreliable Networks
AAAI 2024
Distributed Manifold Hashing for Image Set Classification and Retrieval
AAAI 2024
Incorporating Serverless Computing into P2P Networks for ML Training: In-Database Tasks and Their Scalability Implications (Student Abstract)
AAAI 2024
Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation
AAAI 2024
Exponential Quantum Communication Advantage in Distributed Inference and Learning
NIPS 2024
Federated Learning over Connected Modes
NIPS 2024
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