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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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Fall 2011
A Social Network or Information Network is a structure made up of nodes representing entities, and edges representing the relationships among nodes. Understanding the behaviour of social networks is known as Social Network Analysis (SNA). One of the most important applications of SNA is to find...
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Rationale Extraction and Crohn’s Disease Detection from Computed Tomography Enterography Reports
DownloadFall 2023
Building predictive models with higher predictive performance is the common pursuit in text classification tasks. In almost all domains of text classification problems, the current state-of-the-art models (e.g., Bi-LSTM and BERT) are based on deep neural networks that learn language...
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Fall 2023
Recurrent Neural Networks (RNNs) are typically used to learn representations in partially observable environments. Unfortunately, training RNNs is known to be difficult, and the difficulty increases for agents who learn online and continually interact with the environment. Two common strategies...
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Spring 2015
There is considerable research work going on segmentation of RGB-D clouds due its applications in tasks like scene understanding, robotics etc. The availability of inexpensive and easy to use RGB-D cameras and computational capabilities of GPUs has lead to development of numerous applications in...
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Spring 2018
Hosseinzadeh Heydarabad,Sepideh
In this work we address the problem of fast shadow detection from single images of natural scenes. Different from traditional methods that employ expensive optimization methods, we propose a fast semantic-aware Convolutional Neural Network learning framework which trains on different kinds of...
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Fall 2013
This thesis considers the problem of visualizing simulations of phenomenon which span large ranges of spatial scales. These datasets tend to be extremely large presenting challenges both to human comprehension and high-performance computing. The main problems considered are how to effectively...