Browsing Computer Science by Title
Now showing items 742-761 of 1544
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Large Aperiodic Semigroups
(World Scientific Publishing, 2015-11-01)We search for the largest syntactic semigroups of star-free languages having n left quotients; equivalently, we look for the largest transition semigroups of aperiodic finite automata with n states. We first introduce ... -
Large-Scale Emulation of Anonymous Communication Networks
(University of Waterloo, 2014-08-15)Tor is the most popular low-latency anonymous communication system for the Internet, helping people to protect their privacy online and circumvent Internet censorship. Its low- latency anonymity and distributed design ... -
A Las Vegas Algorithm for the Ordered Majority Problem
(University of Waterloo, 2022-09-29)In this thesis, we study the majority problem using ordered comparisons under the Las Vegas randomized algorithm model. The majority problem asks whether a given set of n elements, each with some colour, has a colour which ... -
Lattice Compression of Polynomial Matrices
(University of Waterloo, 2007-05-01)This thesis investigates lattice compression of polynomial matrices over finite fields. For an m x n matrix, the goal of lattice compression is to find an m x (m+k) matrix, for some relatively small k, such that the ... -
Learn Privacy-friendly Global Gaussian Processes in Federated Learning
(University of Waterloo, 2022-08-17)In the era of big data, Federated Learning (FL) has drawn great attention as it naturally operates on distributed computational resources without the need of data warehousing. Similar to Distributed Learning (DL), FL ... -
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness
(University of Waterloo, 2020-08-19)Deep neural networks have been achieving state-of-the-art performance across a wide variety of applications, and due to their outstanding performance, they are being deployed in safety and security critical systems. However, ... -
Learning Automatic Question Answering from Community Data
(University of Waterloo, 2012-09-19)Although traditional search engines can retrieval thousands or millions of web links related to input keywords, users still need to manually locate answers to their information needs from multiple returned documents or ... -
Learning by Teaching: Key Challenges and Design Implications
(University of Waterloo, 2022-01-17)Benefits of learning by teaching (LbT) have been highlighted by previous studies from a pedagogical lens, as well as through computer-supported systems. However, the challenges that university students face in technology-mediated ... -
Learning Energy-Aware Transaction Scheduling in Database Systems
(University of Waterloo, 2021-09-20)Servers are typically sized to accommodate peak loads, but in practice, they remain under-utilized for much of the time. During periods of low load, there is an opportunity to save power by quickly adjusting processor ... -
Learning Factors and Determining Document-level Satisfaction In Search-as-Learning
(University of Waterloo, 2017-04-26)An important use of search engines is as a tool for learning. Search engines help users find learning material and increases their knowledge in various topics. The underlying process of learning while web searching and ... -
Learning Filters for the 2D Wavelet Transform
(IEEE, 2018)We propose a new method for learning filters for the 2D discrete wavelet transform. We extend our previous work on the 1D wavelet transform in order to process images. We show that the 2D wavelet transform can be represented ... -
Learning from Green Technology Designers
(University of Waterloo, 2014-02-13)This thesis presents results from a qualitative case study on environmentally minded technology designers, and provides an account of how these designers think, differ and behave. Through semi-structured interviews, we ... -
Learning from Partially Labeled Data: Unsupervised and Semi-supervised Learning on Graphs and Learning with Distribution Shifting
(University of Waterloo, 2007-08-20)This thesis focuses on two fundamental machine learning problems:unsupervised learning, where no label information is available, and semi-supervised learning, where a small amount of labels are given in addition to unlabeled ... -
Learning in large-scale spiking neural networks
(University of Waterloo, 2011-08-31)Learning is central to the exploration of intelligence. Psychology and machine learning provide high-level explanations of how rational agents learn. Neuroscience provides low-level descriptions of how the brain changes ... -
Learning Instruction Scheduling Heuristics from Optimal Data
(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 ... -
Learning Sample-Based Monte Carlo Denoising from Noisy Training Data
(University of Waterloo, 2022-02-15)Monte Carlo rendering allows for the production of high-quality photorealistic images of 3D scenes. However, producing noise-free images can take a considerable amount of compute resources. To lessen this burden and speed ... -
Learning Sparse Orthogonal Wavelet Filters
(University of Waterloo, 2018-10-12)The wavelet transform is a well studied and understood analysis technique used in signal processing. In wavelet analysis, signals are represented by a sum of self-similar wavelet and scaling functions. Typically, the wavelet ... -
Learning to Rank in the Age of Muppets
(University of Waterloo, 2022-04-26)The emergence of BERT in 2018 has brought a huge boon to retrieval effectiveness in many tasks across various domains and led the recent research landscape of IR to transformer-related technologies. While researchers ... -
Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search
(ACM, 2022-07)When searching the web for answers to health questions, people can make incorrect decisions that have a negative effect on their lives if the search results contain misinformation. To reduce health misinformation in search ... -
Learning with non-Standard Supervision
(University of Waterloo, 2013-09-26)Machine learning has enjoyed astounding practical success in a wide range of applications in recent years-practical success that often hurries ahead of our theoretical understanding. The standard framework for ...