Now showing items 1-20 of 32

    • Affective Sentiment and Emotional Analysis of Pull Request Comments on GitHub 

      Rishi, Deepak (University of Waterloo, 2017-12-15)
      Sentiment and emotional analysis on online collaborative software development forums can be very useful to gain important insights into the behaviors and personalities of the developers. Such information can later on be ...
    • AlphaStar: Considerations and Human-like Constraints for Deep Learning Game Interfaces 

      Choi, David (University of Waterloo, 2020-12-15)
      Games have historically been a fruitful area for artificial intelligence (AI) research, and StarCraft in particular has been an important grand challenge because of its strategic complexity, multi-agent dynamics, partial ...
    • Applications of Artificial Intelligence to the NHL Entry Draft 

      Alcox, Brandon (University of Waterloo, 2019-01-31)
      This thesis investigates the application of various fields of artificial intelligence to the domain of sports management and analysis. The research in this thesis is primarily focussed on the entry draft for the National ...
    • Applications of Stochastic Gradient Descent to Nonnegative Matrix Factorization 

      Slavin, Matthew (University of Waterloo, 2019-07-15)
      We consider the application of stochastic gradient descent (SGD) to the nonnegative matrix factorization (NMF) problem and the unconstrained low-rank matrix factorization problem. While the literature on the SGD algorithm ...
    • Convex Large Margin Training - Unsupervised, Semi-supervised, and Robust Support Vector Machines 

      Xu, Linli (University of Waterloo, 2007-05-22)
      Support vector machines (SVMs) have been a dominant machine learning technique for more than a decade. The intuitive principle behind SVM training is to find the maximum margin separating hyperplane for a given set of ...
    • Data-Driven Models: An Alternative Discrete Hedging Strategy 

      Nian, Ke (University of Waterloo, 2023-08-16)
      Options hedging is a critical problem in financial risk management. The prevailing approach in financial derivative pricing and hedging has been to first assume a parametric model describing the underlying price dynamics. ...
    • Directly Learning Tractable Models for Sequential Inference and DecisionMaking 

      Melibari, Mazen (University of Waterloo, 2016-06-21)
      Probabilistic graphical models such as Bayesian networks and Markov networks provide a general framework to represent multivariate distributions while exploiting conditional independence. Over the years, many approaches ...
    • Does AI Remember? Neural Networks and the Right to be Forgotten 

      Graves, Laura; Nagisetty, Vineel; Ganesh, Vijay (2020-04-14)
      The Right to be Forgotten is part of the recently enacted General Data Protection Regulation law that affects any data holder that has data on European Union residents. It gives EU residents the ability to request deletion ...
    • Dynamic Security Orchestration System Leveraging Machine Learning 

      Jalalpour, Elaheh (University of Waterloo, 2018-09-20)
      A Content Delivery Network (CDN) employs edge-servers caching content close to end-users to provide high Quality of Service (QoS) in serving digital content. Attacks against edge-servers are known to cause QoS degradation ...
    • Early Warning Signals of Vaccine Scares. 

      Pananos, A. Demetri (University of Waterloo, 2016-09-26)
      There exists strong evidence that vaccines are extremely effective in the prevention of pediatric infectious disease, yet despite this evidence, vaccine refusal is still popular amongst some parents. Existing mathematical ...
    • Evaluating Information Retrieval Systems With Multiple Non-Expert Assessors 

      Li, Le (University of Waterloo, 2013-08-21)
      Many current test collections require the use of expert judgments during construction. The true label of each document is given by an expert assessor. However, the cost and effort associated with expert training and judging ...
    • Finding Cost-Efficient Decision Trees 

      Dufour, David (University of Waterloo, 2014-08-06)
      Decision trees have been a popular machine learning technique for some time. Labelled data, examples each with a vector of values in a feature space, are used to create a structure that can assign a class to unseen examples ...
    • Generalization on Text-based Games using Structured Belief Representations 

      Adhikari, Ashutosh Devendrakumar (University of Waterloo, 2020-12-23)
      Text-based games are complex, interactive simulations where a player is asked to process the text describing the underlying state of the world to issue textual commands for advancing in a game. Playing these games can be ...
    • Harnessing the Power of Generative Models for Mobile Continuous and Implicit Authentication 

      Tahoun, Ezzeldin (University of Waterloo, 2021-06-30)
      Authenticating a user's identity lies at the heart of securing any information system. A trade off exists currently between user experience and the level of security the system abides by. Using Continuous and Implicit ...
    • Increasing the Efficiency of High-Recall Information Retrieval 

      Zhang, Haotian (University of Waterloo, 2019-04-30)
      The goal of high-recall information retrieval (HRIR) is to find all, or nearly all, relevant documents while maintaining reasonable assessment effort. Achieving high recall is a key problem in the use of applications ...
    • Iterative Edit-based Unsupervised Sentence Simplification 

      Kumar, Dhruv (University of Waterloo, 2020-07-28)
      We present a new iterative approach towards unsupervised edit-based sentence simplification. Our approach is guided by a scoring function to select simplified sentences generated after iteratively performing word and ...
    • Learning Instruction Scheduling Heuristics from Optimal Data 

      Russell, Tyrel Clinton (University of Waterloo, 2006)
      The development of modern pipelined and multiple functional unit processors has increased the available instruction level parallelism. In order to fully utilize these resources, compiler writers spend large amounts of ...
    • Lyrics Matter: Using Lyrics to Solve Music Information Retrieval Tasks 

      Singhi, Abhishek (University of Waterloo, 2015-08-06)
      Music Information Retrieval (MIR) research tends to focus on audio features like melody and timbre of songs while largely ignoring lyrics. Lyrics and poetry adhere to a specific rhyme and meter structure which set them ...
    • A Novel Mathematical Framework for the Analysis of Neural Networks 

      Caterini, Anthony (University of Waterloo, 2017-08-22)
      Over the past decade, Deep Neural Networks (DNNs) have become very popular models for processing large amounts of data because of their successful application in a wide variety of fields. These models are layered, often ...
    • Novice-Centric Visualizations for Machine Learning 

      Sun, Yunjia (University of Waterloo, 2016-04-26)
      This thesis focuses on visualizations for machine learning tasks. More specifically, we create a taxonomy for existing machine learning visualizations, and design a system to help machine learning novices perform labelling ...


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