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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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Strengths, Weaknesses, and Combinations of Model-based and Model-free Reinforcement Learning
DownloadSpring 2016
Reinforcement learning algorithms are conventionally divided into two approaches: a model-based approach that builds a model of the environment and then computes a value function from the model, and a model-free approach that directly estimates the value function. The first contribution of this...
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Fall 2021
Structural credit assignment in neural networks is a long-standing problem, with a variety of alternatives to backpropagation proposed to allow for local training of nodes. One of the early strategies was to treat each node as an agent and use a reinforcement learning method called REINFORCE to...
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Spring 2014
All along their lives, individuals take roles in their interactions with each other. This behaviour is known as the role-taking characteristic of human beings. We refer to these roles as social roles that are the primary components of societies. Identifying social roles in a society helps to...
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Fall 2015
Extracting 3D geometry of an object from 2D images has been a popular topic in computer vision for decades. Many methods have been proposed to solve this problem with high accuracy and structured light methods are one of the most commonly used. Despite their high accuracy, there are limitations...
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Fall 2012
In this thesis, we present Structured Message Transport (SMT). SMT is a transport protocol coordinator designed to alleviate the head-of-line blocking problem of existing transport layer protocols including the most widely used, transmission control protocol (TCP). SMT uses explicit dependency...
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Studying Limitations of Generative Transformer based models for Aspect Based Sentiment Analysis
DownloadSpring 2023
Companies can only progress if they understand what their customers feel about their products and services. With companies having an online presence, and with the availability of third-party online reviewing platforms like Yelp, it becomes critical to scour through online reviews. Analysing...
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Spring 2024
In reinforcement learning, agents solve problems through interactions with the environment. However, when faced with intricate environmental dynamics, learning can become challenging, resulting in sub-optimal policies. A potential remedy to this situation lies in the transfer of knowledge from...