Federated learning over images: vertical decompositions and pre-trained backbones are difficult to beat
We carefully evaluate a number of algorithms for learning in a federated environment, and
test their utility for a variety of image classification tasks. We consider many issues that have …
test their utility for a variety of image classification tasks. We consider many issues that have …
Leveraging Sparse Input and Sparse Models: Efficient Distributed Learning in Resource-Constrained Environments
E Kariotakis, G Tsagkatakis… - … on Parsimony and …, 2024 - proceedings.mlr.press
Optimizing for reduced computational and bandwidth resources enables model training in
less-than-ideal environments and paves the way for practical and accessible AI solutions …
less-than-ideal environments and paves the way for practical and accessible AI solutions …
[PDF][PDF] Theories and Perspectives on Practical Deep Learning
CR WOLFE - 2023 - repository.rice.edu
Since not all data can be represented in Euclidean space [26], many applications rely on
graph-structured data. For example, social networks can be modeled as graphs by …
graph-structured data. For example, social networks can be modeled as graphs by …