Now showing items 1963-1982 of 2470

    • Safety-Oriented Stability Biases for Continual Learning 

      Gaurav, Ashish (University of Waterloo, 2020-01-24)
      Continual learning is often confounded by “catastrophic forgetting” that prevents neural networks from learning tasks sequentially. In the case of real world classification systems that are safety-validated prior to ...
    • Sample size and robust marginal methods for cluster-randomized trials with censored event times 

      Cook, Richard J.; Zhong, Yujie (Wiley, 2015-03-15)
      In cluster-randomized trials, intervention effects are often formulated by specifying marginal models, fitting them under a working independence assumption, and using robust variance estimates to address the association ...
    • Santa Claus, Machine Scheduling and Bipartite Hypergraphs 

      Jay, Andrew (University of Waterloo, 2020-01-10)
      Here we discuss two related discrete optimization problems, a prominent problem in scheduling theory, makespan minimization on unrelated parallel machines, and the other a fair allocation problem, the Santa Claus problem. ...
    • Saving Electrical Energy in Commercial Buildings 

      Case, Ryan (University of Waterloo, 2012-08-27)
      With the commercial and institutional building sectors using approximately 29% and 34% of all electrical energy consumption in Canada and the United States, respectively, saving electrical energy in commercial and institutional ...
    • Scala with Explicit Nulls 

      Nieto Rodriguez, Abel (University of Waterloo, 2019-12-20)
      The Scala programming language unifies the object-oriented and functional styles of programming. One common source of errors in Scala programs is null references. In this dissertation, I present a modification to the Scala ...
    • Scalability aspects of data cleaning 

      Saxena, Hemant (University of Waterloo, 2021-01-27)
      Data cleaning has become one of the important pre-processing steps for many data science, data analytics, and machine learning applications. According to a survey by Gartner, more than 25% of the critical data in the world's ...
    • Scalable and Highly Available Database Systems in the Cloud 

      Minhas, Umar Farooq (University of Waterloo, 2013-01-10)
      Cloud computing allows users to tap into a massive pool of shared computing resources such as servers, storage, and network. These resources are provided as a service to the users allowing them to “plug into the cloud” ...
    • Scalable and Holistic Qualitative Data Cleaning 

      Chu, Xu (University of Waterloo, 2017-08-14)
      Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and wrong business decisions. Poor data across businesses and the government cost the ...
    • Scalable and Reliable Middlebox Deployment 

      Ghaznavi, Milad (University of Waterloo, 2020-05-28)
      Middleboxes are pervasive in modern computer networks providing functionalities beyond mere packet forwarding. Load balancers, intrusion detection systems, and network address translators are typical examples of middleboxes. ...
    • Scalable Emulator for Software Defined Networks 

      Roy, Arup Raton (University of Waterloo, 2015-03-30)
      Since its inception, Software Defined Network (SDN) has made itself a very appealing architecture for both Data Center and Wide Area networks by offering more automated control through programmability and simplified network ...
    • Scalable Informative Rule Mining 

      Feng, Guoyao (University of Waterloo, 2016-08-10)
      In this thesis we present SIRUM: a system for Scalable Informative RUle Mining from multi-dimensional data. Informative rules have recently been studied in several contexts, including data summarization, data cube exploration ...
    • A Scalable Partial-Order Data Structure for Distributed-System Observation 

      Ward, Paul (University of Waterloo, 2001)
      Distributed-system observation is foundational to understanding and controlling distributed computations. Existing tools for distributed-system observation are constrained in the size of computation that they can observe ...
    • Scalable Scientific Computing Algorithms Using MapReduce 

      Xiang, Jingen (University of Waterloo, 2013-09-03)
      Cloud computing systems, like MapReduce and Pregel, provide a scalable and fault tolerant environment for running computations at massive scale. However, these systems are designed primarily for data intensive computational ...
    • Scaling Machine Learning Data Repair Systems for Sparse Datasets 

      Attia, Omar (University of Waterloo, 2021-01-21)
      Machine learning data repair systems (e.g. HoloClean) have achieved state-of-the-art performance for the data repair problem on many datasets. However, these systems face significant challenges with sparse datasets. In ...
    • Scalpel: Optimizing Query Streams Using Semantic Prefetching 

      Bowman, Ivan (University of Waterloo, 2005)
      Client applications submit streams of relational queries to database servers. For simple requests, inter-process communication costs account for a significant portion of user-perceived latency. This trend increases ...
    • Scarf's Theorem and Applications in Combinatorics 

      Rioux, Caroline (University of Waterloo, 2006-12-19)
      A theorem due to Scarf in 1967 is examined in detail. Several versions of this theorem exist, some which appear at first unrelated. Two versions can be shown to be equivalent to a result due to Sperner in 1928: for a ...
    • Schema clustering and retrieval for multi-domain pay-as-you-go data intergration systems 

      Mahmoud, Hatem (University of Waterloo, 2010-07-08)
      A data integration system offers a single interface to multiple structured data sources. Many application contexts (e.g., searching structured data on the web) involve the integration of large numbers of structured data ...
    • Score tests based on a finite mixture model of Markov processes under intermittent observation 

      Jiang, Shu; Cook, Richard J. (Wiley, 2019-07-20)
      A mixture model is described, which accommodates different Markov processes governing disease progression in a finite set of latent classes. We give special attention to the setting in which individuals are examined ...
    • Score Tests for Association Under Response-dependent Sampling Designs for Expensive Covariates 

      Lawless, Jerald F. (Oxford Journals, 2015-11-27)
      Response-dependent sampling is widely used in settings where certain variables are expensive to obtain. Estimation has been thoroughly investigated but recent applications have emphasized tests of association for expensive ...
    • Scrappy: Using Scrap Material as Infill to Make Fabrication More Sustainable 

      Wall, Ludwig Wilhelm; Jacobson, Alec; Vogel, Daniel; Schneider, Oliver (ACM Press, 2021-05-06)
      We present a software system for fused deposition modelling 3D printing that replaces infill material with scrap to reduce material and energy consumption. Example scrap objects include unused 3D prints from prototyping ...

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