Now showing items 82-101 of 158

    • Machine learning approaches to challenging problems : interpretable imbalanced classification, interpretable density estimation, and causal inference 

      Goh, Siong Thye (Massachusetts Institute of Technology, 2018)
      In this thesis, I address three challenging machine-learning problems. The first problem that we address is the imbalanced data problem. We propose two algorithms to handle highly imbalanced classification problems. The ...
    • Maintenance scheduling for modular systems-models and algorithms 

      Zarybnisky, Eric J. (Eric Jack), 1979- (Massachusetts Institute of Technology, 2011)
      Maintenance scheduling is an integral part of many complex systems. For instance, without effective maintenance scheduling, the combined effects of preventative and corrective maintenance can have severe impacts on the ...
    • Methods for convex optimization and statistical learning 

      Grigas, Paul (Paul Edward) (Massachusetts Institute of Technology, 2016)
      We present several contributions at the interface of first-order methods for convex optimization and problems in statistical machine learning. In the first part of this thesis, we present new results for the Frank-Wolfe ...
    • The minority achievement gap in a suburban school district 

      Chandler, Lincoln J., 1977- (Massachusetts Institute of Technology, 2008)
      For many decades, the American educational system has yielded significant differences in achievement among students in different racial groups, a phenomenon commonly known as the "Achievement Gap". Despite the volume of ...
    • Mitigating airport congestion : market mechanisms and airline response models 

      Harsha, Pavithra (Massachusetts Institute of Technology, 2009)
      Efficient allocation of scarce resources in networks is an important problem worldwide. In this thesis, we focus on resource allocation problems in a network of congested airports. The increasing demand for access to the ...
    • Mixed-integer convex optimization : outer approximation algorithms and modeling power 

      Lubin, Miles (Miles C.) (Massachusetts Institute of Technology, 2017)
      In this thesis, we study mixed-integer convex optimization, or mixed-integer convex programming (MICP), the class of optimization problems where one seeks to minimize a convex objective function subject to convex constraints ...
    • Modeling and responding to pandemic influenza : importance of population distributional attributes and non-pharmaceutical interventions 

      Nigmatulina, Karima Robert (Massachusetts Institute of Technology, 2009)
      After reviewing prevalent approaches to the modeling pandemic influenza transmission, we present a simple distributional model that captures the most significant population attributes that alter the dynamics of the outbreak. ...
    • Modeling reduction of pandemic influenza using pharmaceutical and non pharmaceutical interventions in a heterogeneous population 

      Teytelman, Anna (Massachusetts Institute of Technology, 2012)
      In an event of a pandemic influenza outbreak such as the great "Spanish Flu" of 1918 and the more recent 2009-2010 H1N1 "Swine Flu" scare, pharmaceutical as well as non-pharmaceutical resources are limited in availability ...
    • Multiserver queueing systems in heavy traffic 

      Eschenfeldt, Patrick Clark (Massachusetts Institute of Technology, 2017)
      In the study of queueing systems, a question of significant current interest is that of large scale behavior, where the size of the system increases without bound. This regime has becoming increasingly relevant with the ...
    • Network flow problems and congestion games : complexity and approximation results 

      Meyers, Carol, Ph. D. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2006)
      (cont.) We first address the complexity of finding an optimal minimum cost solution to a congestion game. We consider both network and general congestion games, and we examine several variants of the problem concerning the ...
    • New algorithms in machine learning with applications in personalized medicine 

      Zhuo, Ying Daisy (Massachusetts Institute of Technology, 2018)
      Recent advances in machine learning and optimization hold much promise for influencing real-world decision making, especially in areas such as health care where abundant data are increasingly being collected. However, ...
    • New applications in Revenue Management 

      Thraves Cortés-Monroy, Charles Mark (Massachusetts Institute of Technology, 2017)
      Revenue Management (RM) is an area with important advances in theory and practice in the last thirty years. This thesis presents three different new applications in RM with a focus on: the firms' perspective, the government's ...
    • New approaches for integrating revenue and supply chain management 

      Elmachtoub, Adam Nabil (Massachusetts Institute of Technology, 2014)
      First, we describe a general framework called online customer selection that describes natural settings where suppliers must actively select which customer requests to serve. Unlike traditional revenue management models ...
    • New neighborhood search algorithms based on exponentially large neighborhoods 

      Ergun, Özlem, 1974- (Massachusetts Institute of Technology, 2001)
      A practical approach for solving computationally intractable problems is to employ heuristic (approximation) algorithms that can find nearly optimal solutions within a reasonable amount of computational time. An improvement ...
    • New procedures for visualizing data and diagnosing regression models 

      Menjoge, Rajiv (Rajiv Shailendra) (Massachusetts Institute of Technology, 2010)
      This thesis presents new methods for exploring data using visualization techniques. The first part of the thesis develops a procedure for visualizing the sampling variability of a plot. The motivation behind this development ...
    • New statistical techniques for designing future generation retirement and insurance solutions 

      Zhu, Zhe (Massachusetts Institute of Technology, 2014)
      This thesis presents new statistical techniques for designing future generation retirement and insurance solutions. It addresses two major challenges for retirement and insurance products: asset allocation and policyholder ...
    • Nonconvex robust optimization 

      Teo, Kwong Meng (Massachusetts Institute of Technology, 2007)
      We propose a novel robust optimization technique, which is applicable to nonconvex and simulation-based problems. Robust optimization finds decisions with the best worst-case performance under uncertainty. If constraints ...
    • Online optimization in routing and scheduling 

      Wagner, Michael R. (Michael Robert), 1978- (Massachusetts Institute of Technology, 2006)
      In this thesis we study online optimization problems in routing and scheduling. An online problem is one where the problem instance is revealed incrementally. Decisions can (and sometimes must) be made before all information ...
    • Online optimization problems 

      Lu, Xin, Ph. D. Massachusetts Institute of Technology. Operations Research Center (Massachusetts Institute of Technology, 2013)
      In this thesis, we study online optimization problems in routing and allocation applications. Online problems are problems where information is revealed incrementally, and decisions must be made before all information is ...
    • Operational decisions and learning for multiproduct retail 

      Pixton, Clark (Clark Charles) (Massachusetts Institute of Technology, 2018)
      We study multi-product revenue management problems, focusing on the role of uncertainty in both the seller and the customer decision processes. We begin by considering a logit model framework for personalized revenue ...