Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Computability, inference and modeling in probabilistic programming

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 135-144).We investigate the class of computable probability distributions and explore the fundamental limitations of using this class to describe and compute conditional distributions. In addition to proving the existence of noncomputable conditional distributions, and thus ruling out the possibility of generic probabilistic inference algorithms (even inefficient ones), we highlight some positive results showing that posterior inference is possible in the presence of additional structure like exchangeability and noise, both of which are common in Bayesian hierarchical modeling. This theoretical work bears on the development of probabilistic programming languages (which enable the specification of complex probabilistic models) and their implementations (which can be used to perform Bayesian reasoning). The probabilistic programming approach is particularly well suited for defining infinite-dimensional, recursively-defined stochastic processes of the sort used in nonparametric Bayesian statistics. We present a new construction of the Mondrian process as a partition-valued Markov process in continuous time, which can be viewed as placing a distribution on an infinite kd-tree data structure.by Daniel M. Roy.Ph.D

Complexity and approximability results for slicing floorplan designs

The first stage in hierarchical approaches to floorplan design determines certain topological relations between the positions of indivisible cells on a VLSI chip. Various optimizations are then performed on this initial layout to minimize certain cost measures such as the chip area. We consider optimization problems in fixing the orientations of the cells and simultaneously fixing the directions of the cuts that are specified by a given slicing tree; the goal is to minimize the area of the chip.\ud \ud We prove that these problems are NP-hard in the ordinary sense, and we describe a pseudo-polynomial time algorithm for them. We also present fully polynomial time approximation schemes for these problems.\u

Complexity and approximability results for slicing floorplan designs

The first stage in hierarchical approaches to floorplan design determines certain topological relations between the positions of indivisible cells on a VLSI chip. Various optimizations are then performed on this initial layout to minimize certain cost measures such as the chip area. We consider optimization problems in fixing the orientations of the cells and simultaneously fixing the directions of the cuts that are specified by a given slicing tree; the goal is to minimize the area of the chip. We prove that these problems are NP-hard in the ordinary sense, and we describe a pseudo-polynomial time algorithm for them. We also present fully polynomial time approximation schemes for these problems. (C) 2002 Elsevier Science B.V. All rights reserved

LIPIcs, Volume 248, ISAAC 2022, Complete Volume

LIPIcs, Volume 248, ISAAC 2022, Complete Volum