We study control of constrained linear systems with only partial statistical information about the uncertainty affecting the system dynamics and the sensor measurements. Specifically, given a finite collection of disturbance realizations drawn from a gener ...
Institute of Electrical and Electronics Engineers (IEEE)2025
Using unprocessed materials in construction is a promising approach to reducing energy and material consumption in the building industry. This paper presents a geometric planning algorithm for constructing multi-leaf masonry walls using natural stones. Our ...
This thesis focuses on the development of advanced algorithmic techniques, primarily Markov Chain Monte Carlo (MCMC) methods, and message passing algorithms, to tackle high-dimensional optimization and inference problems. The algorithms used have a probabi ...
In this work we develop a numerical method for solving a type of convex graph-structured tensor optimization problem. This type of problem, which can be seen as a generalization of multimarginal optimal transport problems with graph-structured costs, appea ...
The convergence of many numerical optimization techniques is highly dependent on the initial guess given to the solver. To address this issue, we propose a novel approach that utilizes tensor methods to initialize existing optimization solvers near global ...
Indonesia is located in a high-seismic-risk region with a significant number of non-engineered houses, which typically have a higher risk during earthquakes. Due to the wide variety of differences even among parameters within one building typology, it is d ...
Multi-energy microgrid (MEMG) has the potential to improve the energy utilization efficiency. However, the uncertainty caused by distributed renewable energy resources brings an urgent need for multi-energy co -optimization to ensure secure operation. This ...
Vulnerable road users (VRUs) constitute an increasing proportion of the annual road fatalities across Europe. One of the crash types involved in these fatalities are blind spot crashes between trucks and bicyclists. Despite the presence of mandatory blind ...
Polarization-adjusted convolutional (PAC) codes are modified polar codes in which a one-to-one convolutional transformation is employed before the classical polar transform. Fano decoding of PAC codes in the Shannon lecture at ISIT2019 showed an outstandin ...
Part I of this paper formulated a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. A diffusion strategy was devised ...
