BibTeX records: V. A. Samaranayake

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@article{DBLP:journals/tnn/KrishnanJS20,
  author    = {Raghavan Krishnan and
               Sarangapani Jagannathan and
               V. A. Samaranayake},
  title     = {Direct Error-Driven Learning for Deep Neural Networks With Applications
               to Big Data},
  journal   = {{IEEE} Trans. Neural Networks Learn. Syst.},
  volume    = {31},
  number    = {5},
  pages     = {1763--1770},
  year      = {2020}
}
@incollection{DBLP:series/sci/KrishnanJS20,
  author    = {Raghavan Krishnan and
               S. Jagannathan and
               V. A. Samaranayake},
  title     = {Direct Error Driven Learning for Classification in Applications Generating
               Big-Data},
  booktitle = {Development and Analysis of Deep Learning Architectures},
  series    = {Studies in Computational Intelligence},
  volume    = {867},
  pages     = {1--29},
  publisher = {Springer},
  year      = {2020}
}
@article{DBLP:journals/bdr/KrishnanSJ19,
  author    = {Raghavan Krishnan and
               V. A. Samaranayake and
               S. Jagannathan},
  title     = {A Hierarchical Dimension Reduction Approach for Big Data with Application
               to Fault Diagnostics},
  journal   = {Big Data Res.},
  volume    = {18},
  year      = {2019}
}
@article{DBLP:journals/tkde/KrishnanSJ19,
  author    = {Raghavan Krishnan and
               V. A. Samaranayake and
               Sarangapani Jagannathan},
  title     = {A Multi-Step Nonlinear Dimension-Reduction Approach with Applications
               to Big Data},
  journal   = {{IEEE} Trans. Knowl. Data Eng.},
  volume    = {31},
  number    = {12},
  pages     = {2249--2261},
  year      = {2019}
}
@inproceedings{DBLP:conf/bigdataconf/KrishnanJS18,
  author    = {Raghavan Krishnan and
               Sarangapani Jagannathan and
               V. A. Samaranayake},
  title     = {A Minimax Approach for Classification with Big-data},
  booktitle = {BigData},
  pages     = {1437--1444},
  publisher = {{IEEE}},
  year      = {2018}
}
@inproceedings{DBLP:conf/bigdataconf/GargKJS18,
  author    = {Shweta Garg and
               Raghavan Krishnan and
               Sarangapani Jagannathan and
               V. A. Samaranayake},
  title     = {Distributed Learning of Deep Sparse Neural Networks for High-dimensional
               Classification},
  booktitle = {BigData},
  pages     = {1587--1592},
  publisher = {{IEEE}},
  year      = {2018}
}
@inproceedings{DBLP:conf/inns/KrishnanSJ18,
  author    = {Raghavan Krishnan and
               V. A. Samaranayake and
               Sarangapani Jagannathan},
  title     = {A Multi-step Nonlinear Dimension-reduction Approach with Applications
               to Bigdata},
  booktitle = {{INNS} Conference on Big Data},
  series    = {Procedia Computer Science},
  volume    = {144},
  pages     = {81--88},
  publisher = {Elsevier},
  year      = {2018}
}
@inproceedings{DBLP:conf/inns/KrishnanJS18,
  author    = {Raghavan Krishnan and
               Sarangapani Jagannathan and
               V. A. Samaranayake},
  title     = {Direct Error Driven Learning for Deep Neural Networks with Applications
               to Bigdata},
  booktitle = {{INNS} Conference on Big Data},
  series    = {Procedia Computer Science},
  volume    = {144},
  pages     = {89--95},
  publisher = {Elsevier},
  year      = {2018}
}
@inproceedings{DBLP:conf/ijcnn/KrishnanJS17,
  author    = {Raghavan Krishnan and
               Sarangapani Jagannathan and
               V. A. Samaranayake},
  title     = {Deep learning inspired prognostics scheme for applications generating
               big data},
  booktitle = {{IJCNN}},
  pages     = {3296--3302},
  publisher = {{IEEE}},
  year      = {2017}
}
@article{DBLP:journals/cssc/MukhopadhyayS10,
  author    = {Purna Mukhopadhyay and
               V. A. Samaranayake},
  title     = {Prediction Intervals for Time Series: {A} Modified Sieve Bootstrap
               Approach},
  journal   = {Commun. Stat. Simul. Comput.},
  volume    = {39},
  number    = {3},
  pages     = {517--538},
  year      = {2010}
}
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