Quantization Robustness of Monotone Operator Equilibrium Networks
Monotone operator equilibrium networks are implicit-layer models whose output is the unique equilibrium of a monotone operator, guaranteeing existence, uniqueness, and convergence. When deployed on low-precision hardware, weights are quantized, potentially destroying these guarantees. We analyze weight quantization as a spectral perturbation of the underlying monotone inclusion. Convergence of the quantized solver is guaranteed whenever the spectral-norm weight perturbation is smaller than the monotonicity margin; the displacement between quantized and full-precision equilibria is bounded in terms of the perturbation size and margin; and a condition number characterizing the ratio of the ...
| Authors | James Li, Philip H. W. Leong, Thomas Chaffey |
|---|---|
| Primary category | math.OC |
| Published | 11 March 2026 |
| Last updated at source | 13 June 2026 |
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