This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
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Skip to Search Results- 83Machine Learning
- 19Artificial Intelligence
- 17Reinforcement Learning
- 9Natural Language Processing
- 8Deep Learning
- 5Computer Vision
- 2Jacobsen, Andrew
- 2Wen, Junfeng
- 1Aghaei, Nikoo
- 1Alam Anik, Md Tanvir
- 1Ashley, Dylan R
- 1Ashrafi Asli, Seyed Arad
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Fall 2019
In this thesis, we investigate different vector step-size adaptation approaches for continual, online prediction problems. Vanilla stochastic gradient descent can be considerably improved by scaling the update with a vector of appropriately chosen step-sizes. Many methods, including AdaGrad,...
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Spring 2021
This thesis evaluated Convoultional LSTM (ConvLSTM) for frame prediction to help better understand motion in neural networks. Three different neural networks were implemented and trained. The three networks included, the original ConvLSTM paper by Shi et al. [35], the Spatio-Temporal network by...
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Spring 2023
Many competitive online video games release new characters on a regular basis. Designing these characters requires significant effort on several aspects including art, story, music, and game balance. Thus automating the design of these aspects offers value in saving human effort. This thesis...