3 citations · 3 across the 9 of their papers we have counts for
9 papers · 1 filter
A particle swarm optimization with a reduced-subspace trust-region safeguard for contact-rich controller tuning
Morteza Kimiaei, Roya Khalili-Amirabadi, Mohsen Jalaeian-Farimani
Contact-rich robotic insertion is challenging because uncertainty in alignment, friction, and contact conditions can lead to unsuccessful assembly, excessive contact forces, and ja…
Risk-Constrained MPPI Tuning with Update-Aware MA-ES Racing
Morteza Kimiaei, Roya Khalili-Amirabadi, Mohsen Jalaeian-Farimani
We formulate offline tuning of Model Predictive Path Integral (MPPI) controllers as a chance-constrained black-box optimization problem and develop an update-aware framework based…
Subspace methods for min-max problems
Morteza Kimiaei, Shima Shabani, Michael Breuß
This paper introduces four groups of subspace methods for nonlinear monotone equations, with applications to large-scale machine learning problems. The methods use Jacobian-free su…
From a Scalar to a Matrix Setting for the Dai--Liao Parameter
Saman Babaie--Kafaki, Morteza Kimiaei, Zohre Aminifard
As is well known, both the numerical performance and the theoretical properties of the Dai--Liao conjugate gradient algorithm are highly dependent on the adjustment of its key para…
A Direction Adaptation Evaluation Strategy for Noisy Derivative-Free Optimization
Morteza Kimiaei, Mahsa Yousefi
In this paper, we develop a direction adaptation evolution strategy (DAES) -- a new MAES-type method -- for noisy derivative-free optimization, designed to reconcile the population…
An Approximate Conjugate Subgradient Algorithm with Matrix Parameter for Derivative-Free Nonsmooth Optimization Problems
Morteza Kimiaei, Saman Babaie-Kafaki, Zohre Aminifard
We propose a derivative-free matrix conjugate-subgradient method for unconstrained nonsmooth optimization of locally Lipschitz functions. The method constructs discrete gradients u…
Reservoir Zero-Coordinatewise Projected Subspace Search for Minimization Over Sparse Symmetric Sets in Machine Learning
Morteza Kimiaei, Shima Shabani, Michael Breuss
We study a class of nonconvex cardinality-constrained optimization problems arising in sparse learning. These problems are NP-hard due to the combinatorial nature of sparsity const…
Diagonal Hessian Approximation Based on Conjugacy Condition for Noisy Derivative-Free Optimization Problems in High Dimensions
Morteza Kimiaei, Saman Babaie--Kafaki
We consider large-scale noisy derivative-free optimization (DFO) problems in which only function values are available and gradient or subgradient information cannot be reliably est…
An efficient penalty decomposition algorithm for minimization over sparse symmetric sets
Ahmad Mousavi, Morteza Kimiaei, Saman Babaie-Kafaki +1
This paper proposes an improved quasi-Newton penalty decomposition algorithm for the minimization of continuously differentiable functions, possibly nonconvex, over sparse symmetri…