Browsing Mathematics (Faculty of) by Subject "optimization"
Now showing items 1-20 of 24
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ClaferMPS: Modeling and Optimizing Automotive Electric/Electronic Architectures Using Domain-Specific Languages
(University of Waterloo, 2017-01-23)Modern automotive electric/electronic (E/E) architectures are growing to the point where architects can no longer manually predict the effects of their design decisions. Thus, in addition to applying an architecture reference ... -
Complexity of Sublinear Algorithms for Convexity in Higher Dimensions
(University of Waterloo, 2022-07-19)Convexity plays a prominent role in both mathematics and computer science. It is defined for sets and functions, and many related problems can be solved efficiently if the set/function is convex. In this thesis, we focus ... -
Computing with Multi-Row Intersection Cuts
(University of Waterloo, 2017-05-16)Cutting planes are one of the main techniques currently used to solve large-scale Mixed-Integer Linear Programming (MIP) models. Many important cuts used in practice, such as Gomory Mixed-Integer (GMI) cuts, are obtained ... -
Convex Algebraic Geometry Approaches to Graph Coloring and Stable Set Problems
(University of Waterloo, 2021-08-23)The objective of a combinatorial optimization problem is to find an element that maximizes a given function defined over a large and possibly high-dimensional finite set. It is often the case that the set is so large that ... -
Error Bounds and Singularity Degree in Semidefinite Programming
(University of Waterloo, 2020-01-24)An important process in optimization is to determine the quality of a proposed solution. This usually entails calculation of the distance of a proposed solution to the optimal set and is referred to as forward error. ... -
An integrated personnel allocation and machine scheduling problem for industrial size multipurpose plants
(Elsevier, 2018-01-01)This paper describes the development and implementation of an optimization model to solve the integrated problem of personnel allocation and machine scheduling for industrial size multipurpose plants. Although each of these ... -
Learning From Almost No Data
(University of Waterloo, 2021-06-15)The tremendous recent growth in the fields of artificial intelligence and machine learning has largely been tied to the availability of big data and massive amounts of compute. The increasingly popular approach of training ... -
Linear Programming Tools and Approximation Algorithms for Combinatorial Optimization
(University of Waterloo, 2010-01-05)We study techniques, approximation algorithms, structural properties and lower bounds related to applications of linear programs in combinatorial optimization. The following "Steiner tree problem" is central: given a graph ... -
Local Graph Clustering Using l1-regularized PageRank Algorithms
(University of Waterloo, 2020-05-05)Local graph clustering methods are used to find small- and medium-scale clusters without traversing the graph. It has been shown that the combination of Approximate Personalized PageRank (APPR) algorithm and sweep method ... -
Matrix Polynomials and their Lower Rank Approximations
(University of Waterloo, 2019-08-07)This thesis is a wide ranging work on computing a “lower-rank” approximation of a matrix polynomial using second-order non-linear optimization techniques. Two notions of rank are investigated. The first is the rank as the ... -
Modelling, Design, and Control of Energy Systems: A Data-Driven Approach
(University of Waterloo, 2019-09-23)In 2018, nearly two-thirds of newly installed global power generation has come from renewable energy sources. Distributed installations of solar photovoltaic (PV) panels have been at the forefront of this global energy ... -
Naive Bayes Data Complexity and Characterization of Optima of the Unsupervised Expected Likelihood
(University of Waterloo, 2017-09-21)The naive Bayes model is a simple model that has been used for many decades, often as a baseline, for both supervised and unsupervised learning. With a latent class variable it is one of the simplest latent variable models, ... -
On the Control of Active End-nodes in the Smart Grid
(University of Waterloo, 2015-08-11)The electrical grid has substantially changed in recent years due to the integration of several disruptive load and generation technologies into low-voltage distribution networks, which are meant to smarten it and improve ... -
Optimal Decumulation for Retirees using Tontines: a Dynamic Neural Network Based Approach
(University of Waterloo, 2023-09-19)We introduce a new approach for optimizing neural networks (NN) using data to solve a stochastic control problem with stochastic constraints. We utilize customized activation functions for the output layers of the NN, ... -
Optimization for Image Segmentation
(University of Waterloo, 2019-06-26)Image segmentation, i.e., assigning each pixel a discrete label, is an essential task in computer vision with lots of applications. Major techniques for segmentation include for example Markov Random Field (MRF), Kernel ... -
Optimization Methods for Semi-Supervised Learning
(University of Waterloo, 2018-05-17)The goal of this thesis is to provide efficient optimization algorithms for some semi-supervised learning (SSL) tasks in machine learning. For many machine learning tasks, training a classifier requires a large amount of ... -
Quantifying the Effects of Solar Panel Orientation on the Electrical Grid
(University of Waterloo, 2016-11-08)As the prices of solar panels continue to decline, energy production from solar farms is skyrocketing, leading to a situation where, at certain times, solar farms produce more energy than can be consumed. Today, the only ... -
Relaxations of the Maximum Flow Minimum Cut Property for Ideal Clutters
(University of Waterloo, 2021-01-29)Given a family of sets, a covering problem consists of finding a minimum cost collection of elements that hits every set. This objective can always be bound by the maximum number of disjoint sets in the family, we refer ... -
Resource optimization for fault-tolerant quantum computing
(University of Waterloo, 2014-01-02)Quantum computing offers the potential for efficiently solving otherwise classically difficult problems, with applications in material and drug design, cryptography, theoretical physics, number theory and more. However, ... -
A Sparse Random Feature Model for Signal Decomposition
(University of Waterloo, 2022-05-11)Signal decomposition and multiscale signal analysis provide useful tools for time-frequency analysis. In this thesis, an overview of the signal decomposition problem is given and popular methods are discussed. A novel ...