15 citations · 86 across the 22 of their papers we have counts for
4 papers · 1 filter
SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition
Hao Li, Zixuan Li, Kenli Li +3
Sparse Tucker Decomposition (STD) algorithms learn a core tensor and a group of factor matrices to obtain an optimal low-rank representation feature for the \underline{H}igh-\under…
An Exploratory Analysis on Users' Contributions in Federated Learning
Jiyue Huang, Rania Talbi, Zilong Zhao +3
Federated Learning is an emerging distributed collaborative learning paradigm adopted by many of today's applications, e.g., keyboard prediction and object recognition. Its core pr…
PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters
Isabelly Rocha, Nathaniel Morris, Lydia Y. Chen +3
DNN learning jobs are common in today's clusters due to the advances in AI driven services such as machine translation and image recognition. The most critical phase of these jobs…
Differential Approximation and Sprinting for Multi-Priority Big Data Engines
Robert Birke, Isabelly Rocha, Juan Perez +3
Today's big data clusters based on the MapReduce paradigm are capable of executing analysis jobs with multiple priorities, providing differential latency guarantees. Traces from pr…