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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 83Machine Learning
- 76Reinforcement Learning
- 42Artificial Intelligence
- 37Machine learning
- 24Natural Language Processing
- 23reinforcement learning
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Fall 2018
Microscopic image analysis is a broad term that covers the use of digital image processing techniques to process and analyze images obtained from a microscope. It is of significant interest to a number of diverse fields such as medicine, biological research, cancer research, drug testing, etc. A...
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Fall 2023
In reinforcement learning (RL), agents learn to maximize a reward signal using nothing but observations from the environment as input to their decision making processes. Whether the agent is simple, consisting of only a policy that maps observations to actions, or complex, containing auxiliary...
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Fall 2014
We study the problem of classifying users in a classified ad network and its applications in further analyzing the network. Specifically, we seek to classify Kijiji users into one of the two business and non-business categories. The problem is challenging due to the sparsity of the data about...
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Fall 2020
In this dissertation we consider the problem of ontology-based data access when the underlying ontology language is represented using tuple-generating dependencies (a term used in theory of databases), also known as existential rules (in the artificial intelligence literature). This problem is...
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Chasing Hallucinated Value: A Pitfall of Dyna Style Algorithms with Imperfect Environment Models
DownloadSpring 2020
In Dyna style algorithms, reinforcement learning (RL) agents use a model of the environment to generate simulated experience. By updating on this simulated experience, Dyna style algorithms allow agents to potentially learn control policies in fewer environment interactions than agents that use...
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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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Fall 2009
Many applications of wireless sensor networks (WSNs) require the sensor nodes of a network to belong to different priority classes where the nodes of a higher priority class enjoy higher data rates than nodes of a lower priority class. Practical design of such networks, however, faces challenges...