4 citations · 18 across the 20 of their papers we have counts for
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Sampling and Optimization meet Enhanced Flows
Yuan Gao, Siming He, Eitan Tadmor
It is well known that the computational realization of Gibbs probability measures, , plays a central role in sampling and optimization. In this paper…
Optimal drift optimizer for non-convex optimization
Qin Li, Sixu Li, Eitan Tadmor +1
We study a finite-horizon stochastic control criterion for non-convex optimization in which Brownian exploration is balanced against a quadratic control cost. Rather than emphasizi…
Swarm-based gradient descent meets simulated annealing
Zhiyan Ding, Martin Guerra, Qin Li +1
We introduce a novel method for non-convex optimization, called Swarm-based Simulated Annealing (SSA), which is at the interface between the swarm-based gradient-descent (SBGD) [J.…
Swarm-based optimization with random descent
Eitan Tadmor, Anil Zenginoglu
We extend our study of the swarm-based gradient descent method for non-convex optimization, [Lu, Tadmor & Zenginoglu, arXiv:2211.17157], to allow random descent directions. We reca…