1 citations · 1 across the 2 of their papers we have counts for
4 papers
The Procrustean Bed of Time Series: The Optimization Bias in Point-wise Loss Functions
Rongyao Cai, Yuxi Wan, Kexin Zhang +6
Intuitively, a more deterministic time series should be easier to forecast. However, point-wise loss functions (e.g., MSE and MAE), serving as differentiable surrogates for the ide…
QiNN-QJ: A Quantum-inspired Neural Network with Quantum Jump for Multimodal Sentiment Analysis
Yiwei Chen, Kehuan Yan, Yu Pan +1
Quantum theory provides non-classical principles, such as superposition and entanglement, that inspires promising paradigms in machine learning. However, most existing quantum-insp…
Fast Numerical Solver of Ising Optimization Problems via Pruning and Domain Selection
Langyu Li, Daoyi Dong, Yu Pan
Quantum annealers, coherent Ising machines and digital Ising machines for solving quantum-inspired optimization problems have been developing rapidly due to their near-term applica…
Local to Global: A Distributed Quantum Approximate Optimization Algorithm for Pseudo-Boolean Optimization Problems
Bo Yue, Shibei Xue, Yu Pan +2
With the rapid advancement of quantum computing, Quantum Approximate Optimization Algorithm (QAOA) is considered as a promising candidate to demonstrate quantum supremacy, which ex…