2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.IR2026
Performance-Driven QUBO for Recommender Systems on Quantum Annealers
Jiayang Niu, Jie Li, Ke Deng +3
Quantum annealers offer a promising hardware platform for solving combinatorial optimization problems, especially those formulated as Quadratic Unconstrained Binary Optimization (Q…
cs.IR2026★ 2 cited
Reproducibility and Artifact Consistency of the SIGIR 2022 Recommender Systems Papers Based on Message Passing
Maurizio Ferrari Dacrema, Michael Benigni, Nicola Ferro
Graph-based techniques relying on neural networks and embeddings have gained attention as a way to develop Recommender Systems (RS) with several papers on the topic presented at SI…