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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 2016
Anomaly detection in time series is one of the fundamental issues in data mining. It addresses various problems in different domains such as intrusion detection in computer networks, anomaly detection in healthcare sensory data, and fraud detection in securities. Though there has been extensive...
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Fall 2013
Time series discords, as introduced in by Keogh et al. [5] is described as the subsequence in the time series which is maximally different from the rest of the subsequences. Discovery of time series discords has been applied to several diverse domains including space shuttle telemetry, industry,...
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Tiny Object Detection in Remote Sensing Images: End-to-End Super-Resolution and Object Detection with Deep Learning
DownloadFall 2020
In this thesis, we study the problem of detecting small objects on low-resolution (LR) satellite imagery. Small-object detection is a challenging problem, especially from LR images. To tackle the challenge, we propose a method to generate super-resolution images from low-resolution images and...
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Fall 2020
As more and more data is collected, individuals and organizations are beginning to share their collected data to gain valuable insights. In doing so, these data stakeholders must be aware of the kind of impact that releasing data will have. Therefore, the misuseability scores M-Score and...
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Spring 2024
Reinforcement learning (RL) has shown great promise in sequential decision-making tasks. However, one of the significant challenges RL faces is poor sample efficiency, which restricts its applicability in many real-world scenarios. Addressing this challenge has the potential to expand the reach...
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Spring 2011
The goal of top-k ranking is to rank individuals so that the best k of them can be determined. Depending on the application domain, an individual can be a person, a product, an event, or just a collection of data or information for which an ordering makes sense. In the context of databases, top-k...
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Fall 2018
With rapidly increasing user-generated geo-tagged content in social media, location-based queries have received more attention lately. There has been extensive work on finding top-K frequent terms in specific locations from social network data streams. However, the problem reverse spatial term...
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Fall 2022
Topic modelling seeks to uncover the conceptual and thematic content of collections of documents. These topics can be used as features for document indexing and classification. However, topic models are increasingly important as tools of applied research. As we seek to develop agents capable of...