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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 2Rabbany khorasgani, Reihaneh
- 2Sacharuk, Edward, 1948-
- 2Sharifi, AmirAli
- 68Machine Learning
- 63Reinforcement Learning
- 41Artificial Intelligence
- 36Machine learning
- 21Natural Language Processing
- 20Image processing. Digital techniques.
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Spring 2023
Traditional survey based methods for clinical depression detection are not always effective; the patient may not reflect their actual mental health condition because of the cognitive bias exhibited while filling out questionnaires about depression. Established through ample earlier work, social...
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Spring 2023
In this thesis, we present Approximation Schemes for the Min Sum k Clustering problem on a number of classes of graph metrics. In Min Sum k Clustering problem introduced by Sahni and Gonzalez [22] in 1976, given a graph G(V, E) with metric edge costs and parameter k, we are asked to partition V...
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Spring 2023
Gradient Descent algorithms suffer many problems when learning representations using fixed neural network architectures, such as reduced plasticity on non-stationary continual tasks and difficulty training sparse architectures from scratch. A common workaround is continuously adapting the neural...
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Spring 2023
This thesis describes the design of a system that is capable of the generation of a Knowledge Graph (KG), referred to as Knowledge Graph Population (KGP), from conversations, specifically with elderly people. While this system still follows a traditional KGP approach with Entity Recognition (ER),...
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Probing the Robustness of Pre-trained Language Models for Structured and Unstructured Entity Matching
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The paradigm of fine-tuning Pre-trained Language Models (PLMs) has been successful in Entity Matching (EM). Many contemporary works leverage PLM-based models to push the state of the results. However, using the power of transformer-based models has some downsides in this task. Despite their...
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Spring 2023
Diffeomorphic image registration is important for medical imaging studies because of the properties like invertibility, smoothness of the transformation, and topology preservation/non-folding of the grid. Violation of these properties can lead to destruction of the neighbourhood and the...
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Spring 2023
Simultaneous Localization and Mapping(SLAM) has been very popular in the past and is gaining more traction in the era of autonomous vehicle research and robot manipulation. Computing accurate surface models from sparse Visual SLAM 3D point clouds is difcult. There have been works where...
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Tile Embeddings: A General Representation for Procedural Level Generation via Machine Learning
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Procedural Level Generation via Machine Learning (PLGML) refers to the application of machine learning techniques to the automated generation of game levels. PLGML researchers have investigated different level generation techniques to generate new game levels matching the style of a training...
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Spring 2023
Reinforcement learning (RL) defines a general computational problem where the learner must learn to make good decisions through interactive experience. To be effective in solving this problem, the learner must be able to explore the environment, make accurate predictions about the future, and...
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Studying Limitations of Generative Transformer based models for Aspect Based Sentiment Analysis
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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...