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Found 5 papers, 4 papers with code
Preconditioned Federated Learning
Federated Learning (FL) is a distributed machine learning approach that enables model training in communication efficient and privacy-preserving manner.
MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classification
MORE adopts the same variational ansatz as binary classifiers while performing multi-classification by fully utilizing the quantum information of a single readout qubit.
Scalable Quantum Neural Networks for Classification
The quantum feature extractors in the SQNN system are independent of each other, so one can flexibly use quantum devices of varying sizes, with larger quantum devices extracting more local features.
LAWS: Look Around and Warm-Start Natural Gradient Descent for Quantum Neural Networks
LAWS is a combinatorial optimization strategy taking advantage of model parameter initialization and fast convergence of QNG.
SAFE: Similarity-Aware Multi-Modal Fake News Detection
Current studies have made significant contributions to predicting fake news with less focus on exploiting the relationship (similarity) between the textual and visual information in news articles.
