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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=benchmark">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=benchmark]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for benchmark]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/463/Nimbus-Scalable-Distributed-In-Memory-Data-Storage"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/442/Cloud-based-Active-Archiving-Solution-for-Databases"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/376/COVER-Model-Pivot-Index-for-Flexible-Adaptable-and-Agile-Systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/330/Map-Reduce-for-Scientific-Applications"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/294/Efficient-Planning-Using-Plan-Libraries-to-Capture-the-Structure-of-the-State-Space"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1048/TDLR-Top-Semantic-Down-Syntactic-Language-Representation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1016/Continuously-Generalized-Ordinal-Regression-for-Linear-and-Deep-Models"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1009/Cybersecurity-Knowledge-Graph-Improvement-with-Graph-Neural-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/897/Reinforcement-Quantum-Annealing-A-Hybrid-Quantum-Learning-Automata"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/890/Leveraging-Artificial-Intelligence-to-Advance-Problem-Solving-with-Quantum-Annealers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/880/Reinforcement-Quantum-Annealing-A-Quantum-Assisted-Learning-Automata-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/878/Scalability-Analysis-of-Blockchain-on-a-Serverless-Cloud"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/932/Convexification-and-Deconvexification-for-Training-Artificial-Neural-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/741/A-database-based-distributed-computation-architecture-with-Accumulo-and-D4M-An-application-of-eigensolver-for-large-sparse-matrix"/>
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 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/463/Nimbus-Scalable-Distributed-In-Memory-Data-Storage">
  <title><![CDATA[Nimbus: Scalable, Distributed, In-Memory Data Storage]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/463/Nimbus-Scalable-Distributed-In-Memory-Data-Storage</link>
  <description><![CDATA[MS Defense

The Apache Hadoop project provides a framework for reliable, scalable, distributed computing. The storage layer of Hadoop, called the Hadoop Distributed File System (HDFS), is an append-only distributed file system designed for commodity hardware. The append-only nature of the file system limits the ability for applications to have random reads and writes of data. This was addressed by Apache HBase and Apache Accumulo, which both allow for quick random access to a highly scalabl...]]></description>
  <dc:date>2013-06-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/442/Cloud-based-Active-Archiving-Solution-for-Databases">
  <title><![CDATA[Cloud based Active Archiving Solution for Databases]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/442/Cloud-based-Active-Archiving-Solution-for-Databases</link>
  <description><![CDATA[In the second talk of the UMBC ACM Student Chapter's Tech Talk Series, ACM Distinguished Speaker Dr. Mukesh Mohania will visit UMBC and talk about "Cloud based Active Archiving Solution for Databases".

Cloud computing offers an exciting opportunity to bring on-demand applications to customers and is being used for delivering hosted services over the Internet and/or processing massive amount of data for business intelligence. In this talk, we will discuss the architecture of cloud computing...]]></description>
  <dc:date>2012-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/376/COVER-Model-Pivot-Index-for-Flexible-Adaptable-and-Agile-Systems">
  <title><![CDATA[COVER Model Pivot Index for Flexible, Adaptable, and Agile Systems]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/376/COVER-Model-Pivot-Index-for-Flexible-Adaptable-and-Agile-Systems</link>
  <description><![CDATA[To support corporate business’ competition on speed to market for product and service development, generically modeled data structures have been  used in the development of vertical application software systems, and in storing XML and RDF data for its flexibility, adaptability, and agility. However, generic data models require multiple self-joins on a single table with a large volume of data, causing slow performance for business intelligence (BI) applications. Conversely, traditional speci...]]></description>
  <dc:date>2010-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/330/Map-Reduce-for-Scientific-Applications">
  <title><![CDATA[Map Reduce for Scientific Applications]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/330/Map-Reduce-for-Scientific-Applications</link>
  <description><![CDATA[In this week's Ebiquity Lab meeting David Chapman will talk about Map Reduce for Scientific Applications
			
Abstract:
Map Reduce is a programming paradigm popularized by google for very large
set computations.  It is a meta algorithm generic enough to solve a large
number of problems.  However, unless care is taken, this generality can
easily come at the price of a significant performance drop.  Current
infrastructure, such as Apache Hadoop, offers a practical solution for
many data ...]]></description>
  <dc:date>2009-11-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/294/Efficient-Planning-Using-Plan-Libraries-to-Capture-the-Structure-of-the-State-Space">
  <title><![CDATA[Efficient Planning Using Plan Libraries to Capture the Structure of the State Space]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/294/Efficient-Planning-Using-Plan-Libraries-to-Capture-the-Structure-of-the-State-Space</link>
  <description><![CDATA[Ph.D. Dissertation Defense

Automated, domain-independent planning is a research area within Artificial Intelligence that is used in a variety of practical applications, especially those for which a large degree of autonomy is required. Planning programs that are given information about the current state of the world, the available actions, and a set of goals that should be achieved. The planner's task is determining the plan: a set of actions and ordering constraints among them. A domain-i...]]></description>
  <dc:date>2009-04-29</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure">
  <title><![CDATA[FALCON: Zero in on the Native Protein Structure]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure</link>
  <description><![CDATA[Protein structure prediction has been a heuristic science.  From homology modeling, threading, to Monte Carlo fragment assembly, decoy clustering, selection, refinement, and consensus, there is no unified model or theory governing the complete process.

We believe the protein structure prediction problem will only be solved by a simple computational model.  We wish to find a single and simple mathematical model that encompasses all of above paradigms and that takes a sequence and converges ...]]></description>
  <dc:date>2008-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants">
  <title><![CDATA[GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants</link>
  <description><![CDATA[Website privacy policies are often lengthy and intricate. Privacy assistants help simplify policies and make them more accessible and user-friendly. The emergence of generative AI (genAI) offers new opportunities to build privacy assistants that can answer users’ questions about privacy policies. However, genAI’s reliability is a concern due to its potential for producing inaccurate information. This study introduces GenAIPABench, a benchmark for evaluating Generative AI-based Privacy Ass...]]></description>
  <dc:date>2024-07-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1048/TDLR-Top-Semantic-Down-Syntactic-Language-Representation">
  <title><![CDATA[TDLR: Top (Semantic)-Down (Syntactic) Language Representation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1048/TDLR-Top-Semantic-Down-Syntactic-Language-Representation</link>
  <description><![CDATA[Language understanding involves processing text with both the grammatical and common-sense contexts of the text fragments. The text “I went to the grocery store and brought home a car” requires both the grammatical context (syntactic) and common-sense context (semantic) to capture the oddity in the sentence. Contextualized text representations learned by Language Models (LMs) are expected to capture a variety of syntactic and semantic contexts from large amounts of training data corpora. ...]]></description>
  <dc:date>2022-11-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1016/Continuously-Generalized-Ordinal-Regression-for-Linear-and-Deep-Models">
  <title><![CDATA[Continuously Generalized Ordinal Regression for Linear and Deep Models]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1016/Continuously-Generalized-Ordinal-Regression-for-Linear-and-Deep-Models</link>
  <description><![CDATA[Ordinal regression is a classification task where classes have an order and prediction error increases the further the predicted class is from the true class. The standard approach for modeling ordinal data involves fitting parallel separating hyperplanes that optimize a certain loss function. This assumption offers sample efficient learning via inductive bias, but is often too restrictive in real-world datasets where features may have varying effects across different categories. Allowing cla...]]></description>
  <dc:date>2022-04-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1009/Cybersecurity-Knowledge-Graph-Improvement-with-Graph-Neural-Networks">
  <title><![CDATA[Cybersecurity Knowledge Graph Improvement with Graph Neural Networks]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1009/Cybersecurity-Knowledge-Graph-Improvement-with-Graph-Neural-Networks</link>
  <description><![CDATA[Cybersecurity Knowledge Graphs (CKGs) help in
aggregating information about cyber-events. CKGs combined
with reasoning and querying systems such as SPARQL enable
security researchers to look up information about past cyberevents
that is helpful in understanding future cyber-events or
drawing similarity with a known cyber-event recorded in a
CKG. CKGs have assertions in the form of semantic triples. The
triples describe a relationship between a subject and object, both
of which are cyb...]]></description>
  <dc:date>2021-12-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/897/Reinforcement-Quantum-Annealing-A-Hybrid-Quantum-Learning-Automata">
  <title><![CDATA[Reinforcement Quantum Annealing: A Hybrid Quantum Learning Automata]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/897/Reinforcement-Quantum-Annealing-A-Hybrid-Quantum-Learning-Automata</link>
  <description><![CDATA[We introduce the notion of reinforcement quantum annealing (RQA) scheme in which an intelligent
agent searches in the space of Hamiltonians and interacts with a quantum annealer that plays the
stochastic environment role of learning automata. At each iteration of RQA, after analyzing results
(samples) from the previous iteration, the agent adjusts the penalty of unsatisfied constraints and
re-casts the given problem to a new Ising Hamiltonian. As a proof-of-concept, we propose a novel
ap...]]></description>
  <dc:date>2020-05-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/890/Leveraging-Artificial-Intelligence-to-Advance-Problem-Solving-with-Quantum-Annealers">
  <title><![CDATA[Leveraging Artificial Intelligence to Advance Problem-Solving with Quantum Annealers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/890/Leveraging-Artificial-Intelligence-to-Advance-Problem-Solving-with-Quantum-Annealers</link>
  <description><![CDATA[We show how to advance quantum information processing, specifically problem-solving with quantum annealers, in the realm of artificial intelligence.  We introduce SAT++, as a novel quantum programming paradigm, that can compile classical algorithms (implemented in classical programming languages) and execute them on quantum annealers.   Moreover, we introduce a post-quantum error correction method that can find samples with significantly lower energy values, compared to the state-of-the-art t...]]></description>
  <dc:date>2020-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/880/Reinforcement-Quantum-Annealing-A-Quantum-Assisted-Learning-Automata-Approach">
  <title><![CDATA[Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/880/Reinforcement-Quantum-Annealing-A-Quantum-Assisted-Learning-Automata-Approach</link>
  <description><![CDATA[Superseded by.:  Ramin Ayanzadeh, Milton Halem, and Tim Finin, Reinforcement Quantum Annealing: A Hybrid Quantum Learning Automata, Nature Scientific Reports, v10, n1, May 2020.




We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning automata and tries to iteratively find better Ising Hamiltonians for the given problem of interest. As a proof-of-concept, we pro...]]></description>
  <dc:date>2020-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/878/Scalability-Analysis-of-Blockchain-on-a-Serverless-Cloud">
  <title><![CDATA[Scalability Analysis of Blockchain on a Serverless Cloud]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/878/Scalability-Analysis-of-Blockchain-on-a-Serverless-Cloud</link>
  <description><![CDATA[While adopting Blockchain technologies to automate their enterprise functionality, organizations are recognizing the challenges of scalability and manual configuration that the state of art present. Scalability of Hyperledger Fabric is an open challenge recognized by the research community. We have automated many of the configuration steps of installing Hyperledger Fabric Blockchain on AWS infrastructure and have benchmarked the scalability of that system. We have used the UCR (University of ...]]></description>
  <dc:date>2019-12-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/932/Convexification-and-Deconvexification-for-Training-Artificial-Neural-Networks">
  <title><![CDATA[Convexification and Deconvexification for Training Artificial Neural Networks]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/932/Convexification-and-Deconvexification-for-Training-Artificial-Neural-Networks</link>
  <description><![CDATA[The purpose of this dissertation research is to overcome a fundamental problem in the theory and application of artificial neural networks (ANNs). The problem, called the local minimum problem in training ANNs, has plagued the ANN community since the middle of 1980s.  ANNs trained with backpropagation are extensively utilized to solve various tasks in artificial intelligence fields for decades. The computing power of ANNs is derived through its particularly distributed structure together with...]]></description>
  <dc:date>2016-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/741/A-database-based-distributed-computation-architecture-with-Accumulo-and-D4M-An-application-of-eigensolver-for-large-sparse-matrix">
  <title><![CDATA[A database-based distributed computation architecture with Accumulo and D4M: An application of eigensolver for large sparse matrix]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/741/A-database-based-distributed-computation-architecture-with-Accumulo-and-D4M-An-application-of-eigensolver-for-large-sparse-matrix</link>
  <description><![CDATA[NoSQL distributed databases have been devised to tackle the challenges resulting from volume, velocity and variety of big data. Graph representation of datasets requires efficient distributed linear algebra operations for large sparse matrix constructed from big data. Storing the transformed matrix into the database not only speeds up the big data analysis process but also facilitates the computation because of indexing. The Hadoop based approach does not natively support iterative algorithms...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
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