3 papers
cs.LG2025
SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
Hong-Ming Chiu, Hao Chen, Huan Zhang +1
Neural network verifiers based on linear bound propagation scale impressively to massive models but can be surprisingly loose when neuron coupling is crucial. Conversely, semidefin…
math.OC2024
Well-conditioned Primal-Dual Interior-point Method for Accurate Low-rank Semidefinite Programming
Hong-Ming Chiu, Richard Y. Zhang
We describe how the low-rank structure in an SDP can be exploited to reduce the per-iteration cost of a convex primal-dual interior-point method down to time and $O(n^{2…
math.OC2023
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent
Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang
Non-convex gradient descent is a common approach for estimating a low-rank ground truth matrix from noisy measurements, because it has per-iteration costs as low as $O(…