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- 7machine learning
- 3artificial intelligence
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- 3optimization
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- 2Ady, Nadia M.
- 2Pilarski, Patrick M.
- 1Bennett, Brendan
- 1Carvalho, Tales Henrique
- 1Chakravarty, Sucheta
- 1Chan, Alan
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Fall 2018
Cognitive radio and energy-harvesting technologies improve the efficiency of spectrum use and energy use in communication networks. However, due to the randomness and dynamics of spectral and energy resources, wireless nodes must intelligently adjust their operating configurations (radio...
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Spring 2020
Machine learning (ML) has shown great potential to create tremendous value and growth to all sectors around the world, enhancing productivity, health, and longevity of humanity. ML differentiates itself from all previous methods through its adaptive and self-learning capabilities. In recent...
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Spring 2023
Finding optimal steam injection policies in the context of Steam Assisted Gravity Drainage (SAGD) represents a major challenge due to the complex dynamics of the process. This complexity is reflected by: i) several concurrent sub-processes, e.g., heat transfer, counter-current flow, imbibition,...
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Spring 2023
The intent of this thesis is to develop a high-performance open-source system that plans with a learned model and to understand the algorithm through extensive analysis. We formulate the problem of maximizing accumulated rewards in Markov Decision Processes, and we frame playing games as such...
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Fall 2023
Real-time strategy games require players to respond to short-term challenges (micromanagement) and long-term objectives (macromanagement) simultaneously to win. However, many players excel at one of these skills but not both. This research studies whether the burden of micromanagement can be...
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Spring 2024
Seismic acquisition constitutes a significant economic commitment, accounting for up to 80% of the overall cost of seismic exploration. This cost is intrinsically linked to the quantity of deployed sensors and sources, each carrying its own set of expenses related to acquisition, deployment, and...
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2017-04-10
Curiosity is a critical component of intelligence. One method of motivating curious behaviour in computational systems is to use reinforcement learning to learn which decisions maximize the amount of unexpected error observed by a predictive component. However, reinforcement learning algorithms...
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Fall 2021
Successful learning is of vital importance to human cognition. Accordingly, researchers have been interested to understand brain-activity signals that support it. However, traditional analysis of brain activity is based on planned comparisons and descriptive methods, which can both overestimate...
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Fall 2023
The transformer architecture is effective in processing sequential data, both because of its ability to leverage parallelism, and because of its self-attention mechanism capable of capturing long-range dependencies. However, the self-attention mechanism is slow for streaming data, that is when...