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Author / Creator / Contributor
- 2Abdi Oskouie, Mina
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 2Rabbany khorasgani, Reihaneh
- 2Sacharuk, Edward, 1948-
- 2Sharifi, AmirAli
Subject / Keyword
- 54Machine Learning
- 48Reinforcement Learning
- 37Artificial Intelligence
- 31Machine learning
- 20Image processing. Digital techniques.
- 18Artificial intelligence
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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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