V. A. Samaranayake

According to our database, V. A. Samaranayake authored at least 13 papers between 2010 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2022

A Game Theoretic Approach for Addressing Domain-Shift in Big-Data.

Krishnan Raghavan, Sarangapani Jagannathan, V. A. Samaranayake

IEEE Trans. Big Data, 2022

2021

Distributed Min-Max Learning Scheme for Neural Networks With Applications to High-Dimensional Classification.

Raghavan Krishnan, Shweta Garg, Sarangapani Jagannathan, V. A. Samaranayake

IEEE Trans. Neural Networks Learn. Syst., 2021

2020

Direct Error Driven Learning for Classification in Applications Generating Big-Data.

Raghavan Krishnan, Sarangapani Jagannathan, V. A. Samaranayake

Proceedings of the Development and Analysis of Deep Learning Architectures, 2020

Direct Error-Driven Learning for Deep Neural Networks With Applications to Big Data.

Raghavan Krishnan, Sarangapani Jagannathan, V. A. Samaranayake

IEEE Trans. Neural Networks Learn. Syst., 2020

2019

A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Big Data.

Raghavan Krishnan, V. A. Samaranayake, Sarangapani Jagannathan

IEEE Trans. Knowl. Data Eng., 2019

A Hierarchical Dimension Reduction Approach for Big Data with Application to Fault Diagnostics.

Raghavan Krishnan, V. A. Samaranayake, Sarangapani Jagannathan

Big Data Res., 2019

2018

A Functional Data Analysis Approach to Traffic Volume Forecasting.

Isaac Michael Wagner-Muns, Ivan G. Guardiola, V. A. Samaranayake, Wasim Irshad Kayani

IEEE Trans. Intell. Transp. Syst., 2018

A Multi-step Nonlinear Dimension-reduction Approach with Applications to Bigdata.

Raghavan Krishnan, V. A. Samaranayake, Sarangapani Jagannathan

Proceedings of the INNS Conference on Big Data and Deep Learning 2018, 2018

Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata.

Raghavan Krishnan, Sarangapani Jagannathan, V. A. Samaranayake

Proceedings of the INNS Conference on Big Data and Deep Learning 2018, 2018

A Minimax Approach for Classification with Big-data.

Raghavan Krishnan, Sarangapani Jagannathan, V. A. Samaranayake

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Distributed Learning of Deep Sparse Neural Networks for High-dimensional Classification.

Shweta Garg, Raghavan Krishnan, Sarangapani Jagannathan, V. A. Samaranayake

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Deep learning inspired prognostics scheme for applications generating big data.

Raghavan Krishnan, Sarangapani Jagannathan, V. A. Samaranayake

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2010

Prediction Intervals for Time Series: A Modified Sieve Bootstrap Approach.

Purna Mukhopadhyay, V. A. Samaranayake

Commun. Stat. Simul. Comput., 2010