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  <title><![CDATA[Generative Adversarial Networks, An Introduction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction</link>
  <description><![CDATA[While deep learning has made historic improvements in speech recognition and object recognition in recent years, almost all of these gains have been in supervised learning of now fairly well understood discriminative models. In the larger context of machine learning, less is understood about both unsupervised and generative models, but Generative Adversarial Networks have emerged as a promising approach to making progress in that direction. 

We are going to introduce Generative Adversarial...]]></description>
  <dc:date>2017-02-01</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/206/Generative-Model-To-Construct-Blog-and-Post-Networks-In-Blogosphere">
  <title><![CDATA[Generative Model To Construct Blog and Post Networks In Blogosphere]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/206/Generative-Model-To-Construct-Blog-and-Post-Networks-In-Blogosphere</link>
  <description><![CDATA[Web graphs have been very useful in the structural and statistical analysis
of the web. Various models have been proposed to simulate web graphs that
generate degree distributions similar to the web. Real world blog networks
resemble many properties of web graphs. But the dynamic nature of the
blogosphere and the link structure evolving due to blog readership and
social interactions is not well expressed by the existing models.

In this research we propose a model for a blogger to cons...]]></description>
  <dc:date>2007-05-01</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1179/KiNETGAN-Enabling-Distributed-Network-Intrusion-Detection-through-Knowledge-Infused-Synthetic-Data-Generation">
  <title><![CDATA[KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1179/KiNETGAN-Enabling-Distributed-Network-Intrusion-Detection-through-Knowledge-Infused-Synthetic-Data-Generation</link>
  <description><![CDATA[In the realm of IoT/CPS systems connected over mobile networks, traditional intrusion detection methods analyze network traffic across multiple devices using anomaly detection techniques to flag potential security threats. However, these methods face significant privacy challenges, particularly with deep packet inspection and network communication analysis. This type of monitoring is highly intrusive, as it involves examining the content of data packets, which can include personal and sensiti...]]></description>
  <dc:date>2024-05-26</dc:date>
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  <title><![CDATA[Knowledge Infusion in Privacy Preserving Data Generation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1136/Knowledge-Infusion-in-Privacy-Preserving-Data-Generation</link>
  <description><![CDATA[Security monitoring is crucial for maintaining a strong IT infrastructure by protecting against emerging threats, identifying vulnerabilities, and detecting potential points of failure. It involves deploying advanced tools to continuously monitor networks, systems, and configurations. However, organizations face challenges in adapting modern techniques like Machine Learning (ML) due to privacy and security risks associated with sharing internal data.  Compliance with regulations like GDPR fur...]]></description>
  <dc:date>2023-08-06</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/382/Second-Space-A-Generative-Model-For-The-Blogosphere">
  <title><![CDATA[Second Space: A Generative Model For The Blogosphere]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/382/Second-Space-A-Generative-Model-For-The-Blogosphere</link>
  <description><![CDATA[Web graphs have been very useful in the structural and statistical analysis of the web. Various models have been proposed to simulate web graphs that generate degree distributions similar to the web. Real world blog networks resemble many properties of web graphs. But the dynamic nature of the blogosphere and the link structure evolving due to blog readership and social interactions is not well expressed by the existing models. In this research we propose a model for a blogger to construct bl...]]></description>
  <dc:date>2008-03-31</dc:date>
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  <title><![CDATA[Generative Model To Construct Blog and Post Networks In Blogosphere]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/363/Generative-Model-To-Construct-Blog-and-Post-Networks-In-Blogosphere</link>
  <description><![CDATA[Web graphs have been very useful in the structural and statistical analysis of the web.
Various models have been proposed to simulate web graphs that generate degree distributions
similar to the web. Real world blog networks resemble many properties of web
graphs. But the dynamic nature of the blogosphere and the link structure evolving due to
blog readership and social interactions is not well expressed by the existing models.
In this research we propose a model for a blogger to constru...]]></description>
  <dc:date>2007-05-01</dc:date>
 </item>
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  <title><![CDATA[Generative Model To Construct Blog and Post Networks In Blogosphere (Masters Thesis Presentation)]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/222/Generative-Model-To-Construct-Blog-and-Post-Networks-In-Blogosphere-Masters-Thesis-Presentation-</link>
  <description><![CDATA[Web graphs have been very useful in the structural and statistical analysis of the web.
Various models have been proposed to simulate web graphs that generate degree distributions similar to the web. Real world blog networks resemble many properties of web graphs. But the dynamic nature of the blogosphere and the link structure evolving due to
blog readership and social interactions is not well expressed by the existing models.

In this research we propose a model for a blogger to constru...]]></description>
  <dc:date>2007-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/221/Generative-Model-To-Construct-Blog-and-Post-Networks-In-Blogosphere-Poster-">
  <title><![CDATA[Generative Model To Construct Blog and Post Networks In Blogosphere (Poster)]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/221/Generative-Model-To-Construct-Blog-and-Post-Networks-In-Blogosphere-Poster-</link>
  <description><![CDATA[Web graphs have been very useful in the structural and statistical analysis of the web.
Various models have been proposed to simulate web graphs that generate degree distributions
similar to the web. Real world blog networks resemble many properties of web
graphs. But the dynamic nature of the blogosphere and the link structure evolving due to
blog readership and social interactions is not well expressed by the existing models.
In this research we propose a model for a blogger to constru...]]></description>
  <dc:date>2007-05-01</dc:date>
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