Browsing Mathematics (Faculty of) by Subject "Machine Learning"
Now showing items 21-32 of 32
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Online Bayesian Learning in Probabilistic Graphical Models using Moment Matching with Applications
(University of Waterloo, 2016-05-18)Probabilistic Graphical Models are often used to e fficiently encode uncertainty in real world problems as probability distributions. Bayesian learning allows us to compute a posterior distribution over the parameters of ... -
The Power Landmark Vector Learning Framework
(University of Waterloo, 2008-05-12)Kernel methods have recently become popular in bioinformatics machine learning. Kernel methods allow linear algorithms to be applied to non-linear learning situations. By using kernels, non-linear learning problems can ... -
Road Condition Sensing Using Deep Learning and Wireless Signals
(University of Waterloo, 2020-08-14)Similar to human car drivers, future driverless cars need to sense the condition of road surfaces so that they can adjust their speed and distance from other cars. This awareness necessitates the need for a sensing mechanism ... -
Social Choice for Partial Preferences Using Imputation
(University of Waterloo, 2016-06-21)Within the field of multiagent systems, the area of computational social choice considers the problems arising when decisions must be made collectively by a group of agents. Usually such systems collect a ranking of the ... -
A Statistical Analysis of the Aggregation of Crowdsourced Labels
(University of Waterloo, 2015-10-29)Crowdsourcing, due to its inexpensive and timely nature, has become a popular method of collecting data that is difficult for computers to generate. We focus on using this method of human computation to gather labels for ... -
Statistical Learning Approaches to Some Classification Problems
(University of Waterloo, 2017-08-01)Classification is essential in statistical learning. This thesis deals with three topics in classification: multi-label classification, nonparametric multi-class classification and a special type of text categorization ... -
StyleCounsel: Seeing the (Random) Forest for the Trees in Adversarial Code Stylometry
(University of Waterloo, 2018-01-12)Authorship attribution has piqued the interest of scholars for centuries, but had historically remained a matter of subjective opinion, based upon examination of handwriting and the physical document. Midway through the ... -
Training of Template-Specific Weighted Energy Function for Sequence-to-Structure Alignment
(University of Waterloo, 2008-09-26)Threading is a protein structure prediction method that uses a library of template protein structures in the following steps: first the target sequence is matched to the template library and the best template structure ... -
Trust Region Methods for Training Neural Networks
(University of Waterloo, 2017-11-09)Artificial feed-forward neural networks (ff-ANNs) serve as powerful machine learning models for supervised classification problems. They have been used to solve problems stretching from natural language processing to ... -
Unsupervised Spectral Ranking For Anomaly Detection
(University of Waterloo, 2014-09-10)Anomaly detection is the problem of finding deviations from expected normal patterns. A wide variety of applications, such as fraud detection for credit cards and insurance, medical image monitoring, network intrusion ... -
Variational Inference for Text Generation: Improving the Posterior
(University of Waterloo, 2020-08-10)Learning useful representations of data is a crucial task in machine learning with wide ranging applications. In this thesis we explore improving representations of models based on variational inference by improving the ... -
Weakly-supervised Semantic Segmentation with Regularized Loss Hyperparameter Search
(University of Waterloo, 2021-09-20)Weakly supervised segmentation signi cantly reduces user annotation e ort. Recently, regularized loss was proposed for single object class segmentation under image-level weak supervision. Regularized loss consists of ...