Jayadeva

Orcid: 0000-0002-0604-8756

According to our database1, Jayadeva authored at least 92 papers between 1992 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks.
Mach. Learn. Sci. Technol., 2024

BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

HybMT: Hybrid Meta-Predictor based ML Algorithm for Fast Test Vector Generation.
Proceedings of the 29th Asia and South Pacific Design Automation Conference, 2024

No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models.
CoRR, 2023

Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics.
CoRR, 2023

Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas.
IEEE Access, 2023

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Block Sparse Variational Bayes Regression Using Matrix Variate Distributions With Application to SSVEP Detection.
IEEE Trans. Neural Networks Learn. Syst., 2022

Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images.
CoRR, 2022

Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors.
CoRR, 2022

A Novel Meta-predictor based Algorithm for Testing VLSI Circuits.
CoRR, 2022

2021
Minimal Complexity Machines Under Weight Quantization.
IEEE Trans. Computers, 2021

Linear time identification of local and global outliers.
Neurocomputing, 2021

Kernel optimization using conformal maps for the minimal complexity machine.
Eng. Appl. Artif. Intell., 2021

Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images.
CoRR, 2021

ComBI: Compressed Binary Search Tree for Approximate <i>k</i>-NN Searches in Hamming Space.
Big Data Res., 2021

Enhash: A Fast Streaming Algorithm For Concept Drift Detection.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020
Neurodynamical classifiers with low model complexity.
Neural Networks, 2020

Sparsity in function and derivative approximation via the empirical feature space.
Inf. Sci., 2020

QMCM: Minimizing Vapnik's bound on the VC dimension.
Neurocomputing, 2020

Complexity Controlled Generative Adversarial Networks.
CoRR, 2020

2019
Twin Neural Networks for the classification of large unbalanced datasets.
Neurocomputing, 2019

Guided Random Forest and its application to data approximation.
CoRR, 2019

Smaller Models, Better Generalization.
CoRR, 2019

Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise.
CoRR, 2019

Learning from Low Training Data using Classifiers with Derivative Constraints.
Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2019

2018
Eigen-MM: EigenAnt Modified Mtsls1 for local search.
Swarm Evol. Comput., 2018

Ultra-Sparse Classifiers Through Minimizing the VC Dimension in the Empirical Feature Space - Submitted to the Special Issue on "Off the Mainstream: Advances in Neural Networks and Machine Learning for Pattern Recognition".
Neural Process. Lett., 2018

Radius-margin bounds for deep neural networks.
CoRR, 2018

EigenSample: A non-iterative technique for adding samples to small datasets.
Appl. Soft Comput., 2018

Some Comments on Variational Bayes Block Sparse Modeling with Correlated Entries.
Proceedings of the Reproducible Research in Pattern Recognition, 2018

Non-Mercer Large Scale Multiclass Least Squares Minimal Complexity Machines.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Twin Neural Networks for Efficient EEG Signal Classification.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Sparse Signal Recovery for Multiple Measurement Vectors with Temporally Correlated Entries: A Bayesian Perspective.
Proceedings of the ICVGIP 2018: 11th Indian Conference on Computer Vision, 2018

Temporal Modeling of EEG Signals using Block Sparse Variational Bayes Framework.
Proceedings of the ICVGIP 2018: 11th Indian Conference on Computer Vision, 2018

Variational Bayes Block Sparse Modeling with Correlated Entries.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017
Twin Support Vector Machines - Models, Extensions and Applications
Studies in Computational Intelligence 659, Springer, ISBN: 978-3-319-46186-1, 2017

Large-Scale Minimal Complexity Machines Using Explicit Feature Maps.
IEEE Trans. Syst. Man Cybern. Syst., 2017

Sparse short-term time series forecasting models via minimum model complexity.
Neurocomputing, 2017

A Data and Model-Parallel, Distributed and Scalable Framework for Training of Deep Networks in Apache Spark.
CoRR, 2017

Scalable Twin Neural Networks for Classification of Unbalanced Data.
CoRR, 2017

Learning Neural Network Classifiers with Low Model Complexity.
CoRR, 2017

2016
Benchmarking NLopt and state-of-the-art algorithms for continuous global optimization via <i>IACO</i><sub>R</sub>.
Swarm Evol. Comput., 2016

Learning a hyperplane regressor through a tight bound on the VC dimension.
Neurocomputing, 2016

Examining Representational Similarity in ConvNets and the Primate Visual Cortex.
CoRR, 2016

Improved sEMG signal classification using the Twin SVM.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

EigenAnt assisted IACOℝ for continuous global optimization.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

2015
Learning a hyperplane classifier by minimizing an exact bound on the VC dimension.
Neurocomputing, 2015

Feature Selection for classification of hyperspectral data by minimizing a tight bound on the VC dimension.
CoRR, 2015

Benchmarking NLopt and state-of-art algorithms for Continuous Global Optimization via Hybrid IACO<sub>ℝ</sub>.
CoRR, 2015

A Neurodynamical System for finding a Minimal VC Dimension Classifier.
CoRR, 2015

Learning a Fuzzy Hyperplane Fat Margin Classifier with Minimum VC dimension.
CoRR, 2015

High performance EEG signal classification using classifiability and the Twin SVM.
Appl. Soft Comput., 2015

The MC-ELM: Learning an ELM-like network with minimum VC dimension.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Enhancing Incremental Ant Colony Algorithm for Continuous Global Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Enhancing IACO<sub>R</sub> Local Search by Mtsls1-BFGS for Continuous Global Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2014
Learning a hyperplane regressor by minimizing an exact bound on the VC dimension.
CoRR, 2014

Feature Selection through Minimization of the VC dimension.
CoRR, 2014

The Coupled EigenAnt algorithm for shortest path problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013
Ants find the shortest path: a mathematical proof.
Swarm Intell., 2013

Biomedical sensor properties of flexible PolyVinyliDene flouride.
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, 2013

Computation and study of the low-frequency oscillation of surface electromyogram recorded in biceps during isometric upper limb contraction.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012
Using Sequential Unconstrained Minimization Techniques to simplify SVM solvers.
Neurocomputing, 2012

2011
Reduced twin support vector regression.
Neurocomputing, 2011

M-Unit EigenAnt: An Ant Algorithm to Find the M Best Solutions.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

Debugging ants: How ants find the shortest route.
Proceedings of the 8th International Conference on Information, 2011

2010
Twin SVM for gesture classification using the surface electromyogram.
IEEE Trans. Inf. Technol. Biomed., 2010

Trail formation in ants. A generalized Polya urn process.
Swarm Intell., 2010

Learning the optimal kernel for Fisher discriminant analysis via second order cone programming.
Eur. J. Oper. Res., 2010

2009
Optimal kernel selection in twin support vector machines.
Optim. Lett., 2009

Regularized least squares fuzzy support vector regression for financial time series forecasting.
Expert Syst. Appl., 2009

Knowledge based proximal support vector machines.
Eur. J. Oper. Res., 2009

Zero Norm Least Squares Proximal SVR.
Proceedings of the Pattern Recognition and Machine Intelligence, 2009

Kernel Optimization Using a Generalized Eigenvalue Approach.
Proceedings of the Pattern Recognition and Machine Intelligence, 2009

2008
Linear potential proximal support vector machines for pattern classification.
Optim. Methods Softw., 2008

Design methodology for configurable analog to digital conversion using support vector machines.
Microelectron. J., 2008

Regularized least squares support vector regression for the simultaneous learning of a function and its derivatives.
Inf. Sci., 2008

Mathematical Modeling and Convergence Analysis of Trail Formation.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
SVM-Based Tree-Type Neural Networks as a Critic in Adaptive Critic Designs for Control.
IEEE Trans. Neural Networks, 2007

Fuzzy multi-category proximal support vector classification via generalized eigenvalues.
Soft Comput., 2007

Twin Support Vector Machines for Pattern Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2007

2006
Regularized Least Squares Twin SVR for the Simultaneous Learning of a Function and its Derivative.
Proceedings of the International Joint Conference on Neural Networks, 2006

Regularized Least Squares Fuzzy Support Vector Regression for Time Series Forecasting.
Proceedings of the International Joint Conference on Neural Networks, 2006

2005
Fuzzy linear proximal support vector machines for multi-category data classification.
Neurocomputing, 2005

Fuzzy Proximal Support Vector Classification Via Generalized Eigenvalues.
Proceedings of the Pattern Recognition and Machine Intelligence, 2005

2004
A neural network with O(N) neurons for ranking N numbers in O(1/N) time.
IEEE Trans. Circuits Syst. I Regul. Pap., 2004

Fast and robust learning through fuzzy linear proximal support vector machines.
Neurocomputing, 2004

2003
Sparse Probability Regression by Label Partitioning.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

1999
Sequential Chaotic Annealing and its Application to Multilayer Channel Routing.
Proceedings of the 12th International Conference on VLSI Design (VLSI Design 1999), 1999

1994
A neural network for the Steiner minimal tree problem.
Biol. Cybern., 1994

1992
Optimization with neural networks: a recipe for improving convergence and solution quality.
Biol. Cybern., 1992


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