Browsing Computer Science by Title
Now showing items 755-774 of 1547
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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 ... -
Learning-Free Methods for Goal Conditioned Reinforcement Learning from Images
(University of Waterloo, 2021-04-27)We are interested in training goal-conditioned reinforcement learning agents to reach arbitrary goals specified as images. In order to make our agent fully general, we provide the agent with only images of the environment ... -
Less is More: Restricted Representations for Better Interpretability and Generalizability
(University of Waterloo, 2023-08-22)Deep neural networks are prevalent in supervised learning for large amounts of tasks such as image classification, machine translation and even scientific discovery. Their success is often at the sacrifice of interpretability ... -
Leveraging Asymmetry and Interdependence to Enhance Social Connectedness in Cooperative Digital Games
(University of Waterloo, 2019-05-24)Play is a fundamental component of human development and is an important means of forming healthy relationships throughout life. Research has shown that the types of digital games people play, how they play them, and who ... -
Leveraging Commodity Photonics to Reduce Datacenter Network Latency
(University of Waterloo, 2014-05-22)Most datacenter network (DCN) designs focus on maximizing bisection bandwidth rather than minimizing server-to-server latency. They are, therefore, ill-suited for important latency-sensitive applications, such as high ... -
Leveraging Software-Defined Networking to Improve Distributed Transaction Processing Performance
(University of Waterloo, 2015-10-28)Recently, software-defined networking (SDN) has been transforming network technologies while NoSQL database systems are on the rise to become the de facto database systems for cloud technologies. Despite the promising ... -
Leveraging Software-Defined Networking to Mask Partial Network Partitions
(University of Waterloo, 2021-08-11)We present an extensive study focused on partial network partitioning. Partial network partitions disrupt the communication between some but not all nodes in a cluster. First, we conduct a comprehensive study of system ... -
Leveraging Watermarks to Improve Performance of Streaming Systems
(University of Waterloo, 2020-05-28)Modern stream processing engines (SPEs) process large volumes of events propagated at high velocity through multiple queries. By continuously receiving watermarks, which are marker events injected into the stream to signify ... -
Lexical Affinities and Language Applications
(University of Waterloo, 2004)Understanding interactions among words is fundamental for natural language applications. However, many statistical NLP methods still ignore this important characteristic of language. For example, information retrieval ... -
LightPlay: An Ambient Light System for Video Game Indicators and Notifications
(University of Waterloo, 2020-08-11)Video games often have indicators and notifications to convey in-game information. However, displaying these visuals on-screen come with trade-offs, such as consuming screen real estate and an inability for them to be ... -
Likelihood-based Density Estimation using Deep Architectures
(University of Waterloo, 2019-12-20)Multivariate density estimation is a central problem in unsupervised machine learning that has been studied immensely in both statistics and machine learning. Several methods have thus been proposed for density estimation ...