Abstract: We consider robust hybrid beamfocusing schemes against statistical and norm-bounded positioning errors in order to improve a total system data rate in near-field communications. To this end, ...

Course in stochastic optimization with an emphasis on formulating, solving, and approximating optimization models under uncertainty. Topics include: Models and applications: extensions of the linear ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...