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Found 4 papers, 1 papers with code
Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection
In this paper, we introduce FedProx+LA, a novel FL method building upon the state-of-the-art FedProx and FedLA to tackle data heterogeneity, which is specifically tailored for vehicular networks.
Fragmented Objects: Boosting Concurrency of Shared Large Objects
This work examines strategies to handle large shared data objects in distributed storage systems (DSS), while boosting the number of concurrent accesses, maintaining strong consistency guarantees, and ensuring good operation performance.
Distributed, Parallel, and Cluster Computing
A Novel Hyperparameter-free Approach to Decision Tree Construction that Avoids Overfitting by Design
Decision trees are an extremely popular machine learning technique.
Superintelligence cannot be contained: Lessons from Computability Theory
Superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.
