Thinh Nguyen-Cong

Differentiable Spectral Normalization for Large-Scale Ising Optimization

Spectral relaxation is widely used for large-scale combinatorial optimization due to its computational efficiency. Yet its effectiveness depends critically on the choice of graph normalization, a design decision typically made heuristically. Here, we show that normalization can be treated as a conti