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Skip to Search Results- 2Abdi Oskouie, Mina
- 1Bell, James M
- 1Bushi, Samuel Suraj
- 1Caminhas, Daniel D.
- 1Chikin, Artem
- 1Cholodovskis Machado, Marlos
- 10Machine Learning
- 7Reinforcement Learning
- 4Artificial Intelligence
- 2Augmented Virtuality
- 2Deep Learning
- 2Emergent Communication
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Fall 2019
Nowadays, the volume of collected data and the size of datasets raise various challenges in the field of data mining. One of such challenges is to, given a dataset, monitor a set of data points and its changes over a period of time. Previously, this monitoring has been done using pattern...
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Fall 2019
Q-learning can be difficult to use in continuous action spaces, because a difficult optimization has to be solved to find the maximal action. Some common strategies have been to discretize the action space, solve the maximization with a powerful optimizer at each step, restrict the functional...
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Addressing the Challenges of Applying Machine Learning for Predicting Mental Disorders and Their Prognosis Using Two Case Studies
DownloadSpring 2019
Ghoreishiamiri, Seyedehreyhaneh
One of the principal applications of machine learning in psychiatry is to build automated tools that can help clinicians predict the diagnosis and prognosis of mental disorders using available data from patients’ profiles. Here, in two different studies, we investigate ways to use machine learn-...
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Fall 2019
Scheduling problems are problems in which jobs are assigned to machines at particular times. A common objective of scheduling is to schedule as many jobs before their deadline as possible, called Throughput Maximization. In this thesis, we provide algorithms for various...
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Spring 2019
With the rise of distributed and global software development, branching has become a popular approach that facilitates collaboration between software developers. Similarly, forking, the practice of cloning an entire repository and creating an independently modified variant of it, is also common....
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Spring 2019
Forouzandehmoghadam, Amirhosein
A biomarker is a feature (e.g., gene expression, SNP, etc.) that is significantly different between two classes of instances – typically case and control. Knowing these biomarkers can help us understand a biological condition or identify the appropriate treatment for a certain disease. Many...
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Spring 2019
Many real-world problems can be formulated as combinatorial optimization problems, thus making it very important to find efficient methods to solve them, both theoretically and practically. In this thesis, we consider several NP-hard combinatorial optimization problems, consisting of some...
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Fall 2019
Occupancy and thermal modelling is the foundation of several smart building applications, such as intelligent control of residential and commercial buildings' Heating, Ventilation and Air Conditioning (HVAC) system to improve energy efficiency and overall occupant experience in the built...
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Fall 2019
We present an algorithm for simultaneously demosaicing digital images, and correcting chromatic aberration, that operates in a latent space of spectral bands. Light refraction by a camera lens system depends on the wavelength of the light, causing relative shifting, and blurring, between...
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Spring 2019
With the burgeoning of online social media and the deluge of information in today's "big data" era, traditional community mining that relies on the connections of the nodes no longer suffices to find communities where the attributes of these nodes play an important role. Though vast research has...