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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 74Machine Learning
- 70Reinforcement Learning
- 41Artificial Intelligence
- 36Machine learning
- 22Natural Language Processing
- 22Reinforcement learning
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Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation
DownloadFall 2021
Modern graphics Application Programming Interfaces (APIs) provide first-class support for ray tracing. Hardware vendors implement drivers for the graphics API including a black-box compiler. The black-box compiler creates architecture-specific binaries that leverage ray-tracing hardware...
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Spring 2024
Retrofitting buildings and optimizing their operation have been at the forefront of global efforts to reduce carbon emissions over the past few decades. Intelligent control of building systems, such as Heating, Ventilation, and Air Conditioning (HVAC), presents two clear benefits: it improves...
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Decision Frequency Adaptation in Reinforcement Learning Using Continuous Options with Open-Loop Policies
DownloadFall 2023
In classic reinforcement learning(RL) for continuous control, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter. Setting it too short may increase the problem’s difficulty by requiring the agent to make numerous decisions...
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Spring 2016
Image classification is an important problem in machine learning. Deep neural networks, particularly deep convolutional networks, have recently contributed great improvements to end-to-end learning quality for this problem. Such networks significantly reduce the need for human designed features...
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Fall 2023
In this thesis, we investigate applying deep learning techniques to learn the win-loss-draw results contained in the databases of the checkers-playing program CHINOOK. Our initial objectives were to (1) compare a deep-learning-based compression scheme versus the custom algorithm used in CHINOOK,...
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Spring 2023
Babiker, Housam Khalifa Bashier
The recent success of deep neural networks has exposed the problem of model transparency. The need for explainability is particularly critical in sensitive domains. In addition, regulatory frameworks for the “responsible” deployment of AI are emerging, creating legal requirements for transparent,...