3 papers
math.OC2026
Order-2 Tightness of Block-Sparse SOS Relaxations for One-Layer ReLU Network Verification with a Matching Input-Sharing Graph
Godai Azuma, Sunyoung Kim, Makoto Yamashita
Azuma, Kim, and Yamashita formulated the verification problem for one-layer ReLU networks as a quadratically constrained quadratic program and established tight semidefinite relaxa…
math.OC2026
Tight Conic Relaxations for Rank-one Doubly Nonnegative Matrix Completion
Godai Azuma, Godai Azura, Sunyoung Kim +1
We study tight conic relaxations for a quadratically constrained quadratic programming (QCQP) formulation of rank-one doubly nonnegative (DNN) matrix completion. Motivated by spars…
math.OC2025
Tight Semidefinite Relaxations for Verifying Robustness of Neural Networks
Godai Azuma, Sunyoung Kim, Makoto Yamashita
For verifying the safety of neural networks (NNs), Fazlyab et al. (2019) introduced a semidefinite programming (SDP) approach called DeepSDP. This formulation can be viewed as the…