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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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Spring 2021
Paraphrasing involves changing the expression of a sentence and rewording it to inform the same information as the original sentence and can occur at word-level, phrase-level, or sentence-level. Paraphrasing task has been attracting attention in recent years as several natural language processing...
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Fall 2020
Many structures in different areas of science can be modeled with graphs containing nodes and edges, which represent the entities of the model and the relationship between them, respectively. Community detection and discovery are two important tasks in Social Network Analysis, which try to find...
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Spring 2019
With the burgeoning of online social media and the deluge of information in today's "big data" era, traditional community mining that relies on the connections of the nodes no longer suffices to find communities where the attributes of these nodes play an important role. Though vast research has...
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Fall 2015
Information networks that describe the relationship between individuals are called social networks and are usually modeled by a graph structure. Social network analysis is the study of these information networks which leads to uncovering patterns of interaction among the entities. Community...
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Fall 2010
Information networks represent relations in data, relationships typically ignored in iid (independent and identically distributed) data. Such networks abound, like coauthorships in bibliometrics, cellphone call graphs in telecommunication, students interactions in Education, etc. A large body of...
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Fall 2010
Much structured data of scientific interest can be represented as networks, where sets of nodes or vertices are joined together in pairs by links or edges. Although these networks may belong to different research areas, there is one property that many of them do have in common: the network...
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Spring 2012
Social networks are ubiquitous. They can be extracted from our purchase history at on-line retailers, our cellphone bills, and even our health records. Mining tech- niques that can accurately and efficiently identify interesting patterns in these net- works are sought after by researchers from a...
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Fall 2018
There is no shortage of community mining algorithms for discovering structure in complex information networks; most with unique advantages, however, all with drawbacks, including efficiency, correctness, resolution limit, and field of view limit. We introduce a novel efficient approach for...
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Spring 2023
Predicting a dense depth map from LiDAR scans and synced RGB images with a small deep neural network is a challenging task. Most top-accuracy methods boost precision by having a very large number of parameters and as a result huge memory consumption. Whereas, depth completion tasks are commonly...