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- 26Artificial Intelligence
- 23Reinforcement Learning
- 21Deep Learning
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- 165Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8Computing Science, Department of
- 7Computing Science, Department of/Technical Reports (Computing Science)
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2011
Technical report TR11-01. Causality is a fundamental concept in reasoning. The effectiveness of many reasoning tasks depends on the understanding of the underlying cause-effect relationships. Therefore, the notion of causality has been explored in a wide range of disciplines. Causal discovery,...
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Fall 2024
Numerical simulation is extensively used in advanced analysis of structures under seismic loading. Even though computational power and solution algorithms have advanced over the years, response evaluation of complex structures using numerical methods can still be challenging due to high...
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Technical Efficiency of Wildfire Detection and Machine Learning Predictions in Alberta, Canada
DownloadSpring 2024
Wildfire management agencies must continue to evolve and adjust to the dynamic nature of their industry. They face pressures that include a changing climate with the prospect of intense future fire seasons, tighter government budgets for wildfire detection and suppression, and the fast-pace of...
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Fall 2022
A number of architectures and time series forecasting algorithms use complex fuzzy sets, which are extensions of type-1 fuzzy sets. In the complex fuzzy set literature, the two most common forms of fuzzy sets are sinusoidal membership functions and complex Gaussian membership one. However, there...
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Spring 2018
Patients with Type I Diabetes (T1D) must take insulin injections to prevent the serious long term effects of hyperglycemia â high blood glucose (BG). These patients must also be careful not to inject too much insulin because this could induce hypoglycemia (low BG), which can be fatal. Patients...
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The Contrastive Gap: A New Perspective on the ‘Modality Gap’ in Multimodal Contrastive Learning
DownloadFall 2024
Learning jointly from images and texts using contrastive pre-training has emerged as an effective method to train large-scale models with a strong grasp of semantic image concepts. For instance, CLIP, pre-trained on a large corpus of web data, excels in tasks like zero-shot image classification,...
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2013
Abou-Moustafa, Karim T., Kozyrskyj, Anita, Guttman, David, Scott, James, Yasui, Yutaka
Entropy measures of probability distributions are widely used measures in ecology, biology, genetics, and in other fields, to quantify species diversity of a community. Unfortunately, entropy–based diversity indices, or diversity indices for short, suffer from three problems. First, when...
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The Estimation of Buttresses Volume and Classification of Leaf, Wood, and Lianas from Terrestrial Laser Scanning data
DownloadSpring 2023
Forests account for one third of land area, and two third of global photosynthesis. The better we know about forests, the better decisions we can make on forest management and carbon cycle modeling. During the last decades, we see the development in remote sensing techniques for forest...
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Fall 2020
We explore the interplay of generate-and-test and gradient-descent techniques for solving online supervised learning problems. The task in supervised learning is to learn a function using samples of inputs to output pairs. This function is called the target function. The standard way to learn...