IEEE

Dataset Distillation-Based Hybrid Federated Learning on Non-IID Data

Abstract: In federated learning, the heterogeneity of client data has a great impact on the performance of model training. Many heterogeneity issues in this process are raised by non-independently and ...
drugtargetreview.com

From fragments to maps: scaling drug–target interaction data

Most drug–target data were never designed to be compared at scale. Pharmome mapping takes a different approach, building a shared dataset intended to support more predictable discovery. Drug discovery ...
IEEE

A Comprehensive Survey on Machine and Deep Learning for Optical Communications

Abstract: The increasing complexity of optical communication systems and networks necessitates advanced methodologies for extracting valuable insights from vast and heterogeneous datasets. Machine ...
Frontiers

Dataset for the adapted Strategy Inventory for Language Learning

This Data Report documents a dataset that was collected for the purposes of adapting and validating the SILL–JP/STEM instrument, a Japanese-language version of Oxford's Strategy Inventory for Language ...