Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of items of interest, subject to a space constraint. We show that in many important applications, one faces variants of this basic problem, in which the individual items are sets themselves, and each set is associated with ...

In a previous paper [Constrained Hardy Space Approximation, preprint available at http://www.mathematik.uni-karlsruhe.de/iwrmm/seite/ preprints/] we considered the problem of minimizing the distance ‖f − φ‖Lp(K), where K is a subset of the complex unit circle ∂D and φ ∈ C(K), subject to the constraint that f lies in the Hardy space H(D) and |f | ≤ g for some positive function g. This problem oc...

Constrained State-space Model Predictive Control is presented in the paper. Predictive controller based on incremental linear state-space process model and quadratic criterion is derived. Typical types of constraints are considered – limits on manipulated, state and controlled variables. Control experiments with nonlinear model of multivariable laboratory process are simulated first and real ex...

During 1990, in response to the common problem of a filled hard disk, I became obsessed with the idea of producing a compact visualization of directory tree structures. Since the 80 Megabyte hard disk in the HCIL was shared by 14 users it was difficult to determine how and where space was used. Finding large files that could be deleted, or even determining which users consumed the largest share...

During 1990, in response to the common problem of a filled hard disk, I became obsessed with the idea of producing a compact visualization of directory tree structures. Since the 80 Megabyte hard disk in the HCIL was shared by 14 users it was difficult to determine how and where space was used. Finding large files that could be deleted, or even determining which users consumed the largest share...

In this paper, the trajectory tracking problem of a nonlinear robotic system with 3DOFs under control signal obtained through nonlinearly constrained state spaceIterative Learning Control (ILC) methods is considered. The focus paper analysis different parameters on convergence rate two space ILCalgorithms: Bounded Error Algorithm (BEAILC) and Constrained Output algorithm (COILC), as well compar...

Abstract Financial portfolio managers typically face multi-period optimization tasks such as short-selling or investing at least a particular portion of the in specific industry sector. A common approach to tackle these problems is use constrained Markov decision process (CMDP) methods, which may suffer from sample inefficiency, hyperparameter tuning, and lack guarantees for constraint violatio...