4 papers
IRON: Implicit Resolvent Optimization under Noise
Valentin Leplat, Roland Hildebrand
We study stochastic optimization from a joint continuous-discrete point of view. Starting from a second-order stochastic differential equation interpreted as a noisy accelerated gr…
Speeding up the Goemans-Williamson randomized procedure by difference-of-convex optimization
Hadi Salloum, Roland Hildebrand, Nhat Trung Nguyen +4
We present a novel approach to accelerate the Goemans-Williamson (GW) randomized rounding procedure for quadratic unconstrained binary optimization (QUBO) problems. Instead of solv…
Norm-Constrained Flows and Sign-Based Optimization: Theory and Algorithms
Valentin Leplat, Sergio Mayorga, Roland Hildebrand +1
Sign Gradient Descent (SignGD) uses only the coordinate-wise sign of the gradient. We study this method through norm-constrained continuous-time dynamics: at each point, the veloci…
Mixed Newton Method for Optimization in Complex Spaces
Nikita Yudin, Roland Hildebrand, Sergey Bakhurin +5
In this paper, we modify and apply the recently introduced Mixed Newton Method, which is originally designed for minimizing real-valued functions of complex variables, to the minim…