Now showing items 1277-1296 of 2985

    • Implied Volatility Modelling 

      Zhu, Anyi (University of Waterloo, 2014-01-08)
      We propose extensions on calibrating the volatility surface through multi-factor regression models. The proposed models are back-tested against the historical S&P 500 prices during both the volatile and non-volatile periods ...
    • Importance Sampling and Stratification for Copula Models 

      Arbenz, Philipp; Cambou, Mathieu; Hofert, Marius; Lemieux, Christiane; Taniguchi, Yoshihiro (Springer, 2018)
      An importance sampling approach for sampling from copula models is introduced. The proposed algorithm improves Monte Carlo estimators when the functional of interest depends mainly on the behaviour of the underlying random ...
    • Importance Sampling and Stratification Techniques for Multivariate Models with Low-Dimentional Structures 

      Taniguchi, Yoshihiro (University of Waterloo, 2017-12-22)
      Many problems in finance and risk management involve the computation of quantities related to rare-event analysis. As many financial problems are high-dimensional, the quan- tities of interest rarely have analytical forms ...
    • The Impress Context Store: A Coordination Framework for Context-Aware Systems 

      Li, Herman Hon Yu (University of Waterloo, 2006)
      The dream of weaving technology into our everyday fabric of life is recently being made possible by advances in ubiquitous computing and sensor technologies. Countless sensors of various sizes have made their way into ...
    • An Improved Algorithm for Tor Circuit Scheduling 

      Tang, Can (University of Waterloo, 2010-07-08)
      Tor is a popular anonymity-preserving network, consisting of routers run by volunteers all around the world. It protects Internet users’ privacy by relaying their network traffic through a series of routers, thus concealing ...
    • Improved approximation guarantees for lower-bounded facility location problem 

      Ahmadian, Sara (University of Waterloo, 2010-09-28)
      We consider the lower-bounded facility location (LBFL) problem (, also known as load-balanced facility location), which is a generalization of uncapacitated facility location (UFL) problem where each open facility is ...
    • Improved Bayesian Network Structure Learning in the Model Averaging Paradigm 

      Liao, Zhenyu (University of Waterloo, 2023-01-10)
      A Bayesian network (BN) is a probabilistic graphical model with applications in knowledge discovery and prediction. Its structure can be learned from data using the well-known score-and-search approach, where a scoring ...
    • Improved Diagnostics & Performance for Quantum Error Correction 

      Jain, Aditya (University of Waterloo, 2023-08-04)
      Building large scale quantum computers is one of the most exciting ventures being pursued by researchers in the 21st century. However, the presence of noise in quantum systems poses a major hindrance towards this ambitious ...
    • Improved Model Poisoning Attacks and Defenses in Federated Learning with Clustering 

      Li, Xinda (University of Waterloo, 2022-05-12)
      Federated Learning (FL) allows multiple participants to collaboratively train a deep learning model without sharing their private training data. However, due to its distributive nature, FL is vulnerable to various poisoning ...
    • Improved Particle Filter Based Localization and Mapping Techniques 

      Milstein, Adam (University of Waterloo, 2008-04-28)
      One of the most fundamental problems in mobile robotics is localization. The solution to most problems requires that the robot first determine its location in the environment. Even if the absolute position is not necessary, ...
    • Improved Scalability and Accuracy of Bayesian Network Structure Learning in the Score-and-Search Paradigm 

      Sharma, Charupriya (University of Waterloo, 2023-05-16)
      A Bayesian network is a probabilistic graphical model that consists of a directed acyclic graph (DAG), where each node is a random variable and attached to each node is a conditional probability distribution (CPD). A ...
    • Improvements in the Accuracy of Pairwise Genomic Alignment 

      Hudek, Alexander Karl (University of Waterloo, 2010-04-16)
      Pairwise sequence alignment is a fundamental problem in bioinformatics with wide applicability. This thesis presents three new algorithms for this well-studied problem. First, we present a new algorithm, RDA, which aligns ...
    • Improvements to Many-Sorted Finite Model Finding using SMT Solvers 

      Zila, Owen (University of Waterloo, 2023-08-17)
      Formal modeling is a powerful tool in requirements engineering. By modeling a system before implementation, one can discover bugs before they appear in testing or production. Model finding (or instance finding) for a model ...
    • Improvements to Transitive-Closure-based Model Checking in Alloy 

      Farheen, Sabria (University of Waterloo, 2018-01-19)
      Model checking, which refers to the verification of temporal properties of a transition system, is a common formal method for verifying models. Transitive-closure-based model checking (TCMC), developed by Vakili et al., ...
    • Improving Artificial Neural Network Models for Predicting Hourly Water Consumption 

      WANG, LI (University of Waterloo, 2018-09-26)
      Smart water meter devices are now widely installed in single family residences, allowing water consumption data to be collected at a high resolution from both the temporal and spatial perspectives. Such data allows improved ...
    • Improving Cluster Scheduling Resiliency to Network Faults 

      Qunaibi, Sara (University of Waterloo, 2023-05-31)
      We present a comprehensive empirical study of the impact partial network partitions have on cluster managers in data analysis frameworks. Our study shows that modern scheduling approaches are vulnerable to partial network ...
    • Improving Coarsening and Interpolation for Algebraic Multigrid 

      Butler, Jeffrey (University of Waterloo, 2006)
      Algebraic multigrid (AMG) is one of the most efficient algorithms for solving large sparse linear systems on unstructured grids. Classical coarsening schemes such as the standard Ruge-Stüben method [14] can lead ...
    • Improving Convergence Rates in Multiagent Learning Through Experts and Adaptive Consultation 

      Hines, Greg (University of Waterloo, 2007-05-07)
      Multiagent learning (MAL) is the study of agents learning while in the presence of other agents who are also learning. As a field, MAL is built upon work done in both artificial intelligence and game theory. Game theory ...
    • Improving Data Locality in Applications through Execution Delegation 

      Curto, Bryant J (University of Waterloo, 2023-01-09)
      With the slowing or even death of Moore’s Law, computer system architectures are trending toward more CPU cores. This trend has driven systems researchers to explore novel ways of utilizing this computational power for ...
    • Improving Data Locality in Applications using Message Passing 

      Srinivasan, Priyaa Varshinee (University of Waterloo, 2014-12-04)
      This thesis presents a systematic study of two modes of program execution: synchronous and asynchronous. In synchronous mode, program components are tightly coupled. Traditional procedure call represents the synchronous ...

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