Jayadeva

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 49

Top Topics

Variational Bayes

Top Venues

Swarm Evol. Comput.

Publications

Suresh Bishnoi, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics. ICLR (2024)
Nimesh Agrawal, Anuj Kumar Sirohi, Sandeep Kumar, Jayadeva
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation. AAAI (2024)
Shruti Pandey, Jayadeva, Smruti R. Sarangi
HybMT: Hybrid Meta-Predictor based ML Algorithm for Fast Test Vector Generation. ASPDAC (2024)
Nimesh Agrawal, Anuj Kumar Sirohi, Jayadeva, Sandeep Kumar
No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation. CoRR (2023)
Debanjali Sarkar, Taimoor Khan, Jayadeva, Ahmed A. Kishk
Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas. IEEE Access 11 (2023)
Suresh Bishnoi, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics. CoRR (2023)
Mohd Zaki, Jayadeva, Mausam, N. M. Anoop Krishnan
MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models. CoRR (2023)
Suresh Bishnoi, Ravinder Bhattoo, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks. CoRR (2023)
Suresh Bishnoi, Ravinder Bhattoo, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems. ICLR (2023)
Shruti Sharma, Santanu Chaudhury, Jayadeva
Block Sparse Variational Bayes Regression Using Matrix Variate Distributions With Application to SSVEP Detection. IEEE Trans. Neural Networks Learn. Syst. 33 (1) (2022)
Mohd Zaki, Siddhant Sharma, Sunil Kumar Gurjar, Raju Goyal, Jayadeva, N. M. Anoop Krishnan
Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images. CoRR (2022)
Shruti Pandey, Jayadeva, Smruti R. Sarangi
A Novel Meta-predictor based Algorithm for Testing VLSI Circuits. CoRR (2022)
Suresh Bishnoi, Skyler Badge, Jayadeva, N. M. Anoop Krishnan
Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors. CoRR (2022)
Skyler Badge, Sumit Soman, Suresh Chandra, Jayadeva
Kernel optimization using conformal maps for the minimal complexity machine. Eng. Appl. Artif. Intell. 106 (2021)
Aashi Jindal, Prashant Gupta, Debarka Sengupta, Jayadeva
Enhash: A Fast Streaming Algorithm For Concept Drift Detection. ESANN (2021)
Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
Linear time identification of local and global outliers. Neurocomputing 429 (2021)
Mayank Sharma, Sumit Soman, Jayadeva
Minimal Complexity Machines Under Weight Quantization. IEEE Trans. Computers 70 (8) (2021)
Kartikeya Badola, Sameer Ambekar, Himanshu Pant, Sumit Soman, Anuradha Sural, Rajiv Narang, Suresh Chandra, Jayadeva
Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images. CoRR (2021)
Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
-NN Searches in Hamming Space. Big Data Res. 25 (2021)
Sumit Soman, Jayadeva, Rajat Thakur, Mayank Sharma, Suresh Chandra
Sparsity in function and derivative approximation via the empirical feature space. Inf. Sci. 512 (2020)
Himanshu Pant, Jayadeva, Sumit Soman
Complexity Controlled Generative Adversarial Networks. CoRR (2020)
Himanshu Pant, Sumit Soman, Jayadeva, Amit Bhaya
Neurodynamical classifiers with low model complexity. Neural Networks 132 (2020)
Jayadeva, Sumit Soman, Himanshu Pant, Mayank Sharma
QMCM: Minimizing Vapnik's bound on the VC dimension. Neurocomputing 399 (2020)
Aashi Jindal, Prashant Gupta, Debarka Sengupta, Jayadeva
Enhash: A Fast Streaming Algorithm For Concept Drift Detection. CoRR (2020)
Mayank Sharma, Aayush Yadav, Sumit Soman, Jayadeva
Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise. CoRR (2019)
Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
Guided Random Forest and its application to data approximation. CoRR (2019)
Jayadeva, Himanshu Pant, Mayank Sharma, Sumit Soman
Twin Neural Networks for the classification of large unbalanced datasets. Neurocomputing 343 (2019)
Mayank Sharma, Suraj Tripathi, Abhimanyu Dubey, Jayadeva, Sai Guruju, Nihal Goalla
Smaller Models, Better Generalization. CoRR (2019)
Sumit Soman, Jayadeva
Learning from Low Training Data using Classifiers with Derivative Constraints. COMAD/CODS (2019)
Shruti Sharma, Santanu Chaudhury, Jayadeva
Variational Bayes Block Sparse Modeling with Correlated Entries. ICPR (2018)
Shruti Sharma, Santanu Chaudhury, Jayadeva, Snigdha Bhagat
Sparse Signal Recovery for Multiple Measurement Vectors with Temporally Correlated Entries: A Bayesian Perspective. ICVGIP (2018)
Jayadeva, Mayank Sharma, Sumit Soman, Himanshu Pant
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. 48 (2) (2018)
Mayank Sharma, Jayadeva, Sumit Soman
Radius-margin bounds for deep neural networks. CoRR (2018)
Shruti Sharma, Santanu Chaudhury, Jayadeva
Some Comments on Variational Bayes Block Sparse Modeling with Correlated Entries. RRPR (2018)
Jayadeva, Sumit Soman, Soumya Saxena
EigenSample: A non-iterative technique for adding samples to small datasets. Appl. Soft Comput. 70 (2018)
Udit Kumar, Sumit Soman, Jayadeva
Eigen-MM: EigenAnt Modified Mtsls1 for local search. Swarm Evol. Comput. 43 (2018)
Mayank Sharma, Sumit Soman, Jayadeva, Himanshu Pant
Non-Mercer Large Scale Multiclass Least Squares Minimal Complexity Machines. IJCNN (2018)
Himanshu Pant, Sumit Soman, Jayadeva, Mayank Sharma
Twin Neural Networks for Efficient EEG Signal Classification. IJCNN (2018)
Shruti Sharma, Santanu Chaudhury, Jayadeva
Temporal Modeling of EEG Signals using Block Sparse Variational Bayes Framework. ICVGIP (2018)
Pawas Gupta, Sanjit S. Batra, Jayadeva
Sparse short-term time series forecasting models via minimum model complexity. Neurocomputing 243 (2017)
Jayadeva, Himanshu Pant, Mayank Sharma, Abhimanyu Dubey, Sumit Soman, Sai Guruju, Nihal Goalla
Learning Neural Network Classifiers with Low Model Complexity. CoRR (2017)
Himanshu Pant, Jayadeva, Sumit Soman, Mayank Sharma
Scalable Twin Neural Networks for Classification of Unbalanced Data. CoRR (2017)
Mayank Sharma, Jayadeva, Sumit Soman, Himanshu Pant
Large-Scale Minimal Complexity Machines Using Explicit Feature Maps. IEEE Trans. Syst. Man Cybern. Syst. 47 (10) (2017)
Disha Shrivastava, Santanu Chaudhury, Jayadeva
A Data and Model-Parallel, Distributed and Scalable Framework for Training of Deep Networks in Apache Spark. CoRR (2017)
Abhimanyu Dubey, Jayadeva, Sumeet Agarwal
Examining Representational Similarity in ConvNets and the Primate Visual Cortex. CoRR (2016)
Udit Kumar, Sumit Soman, Jayadeva
EigenAnt assisted IACOℝ for continuous global optimization. SMC (2016)
Sumit Soman, Jayadeva, Sridhar P. Arjunan, Dinesh Kant Kumar
Improved sEMG signal classification using the Twin SVM. SMC (2016)
Udit Kumar, Sumit Soman, Jayadeva
. Swarm Evol. Comput. 27 (2016)
Jayadeva, Suresh Chandra, Sanjit S. Batra, Siddarth Sabharwal
Learning a hyperplane regressor through a tight bound on the VC dimension. Neurocomputing 171 (2016)
Sumit Soman, Jayadeva
High performance EEG signal classification using classifiability and the Twin SVM. Appl. Soft Comput. 30 (2015)
Udit Kumar, Jayadeva, Sumit Soman
Local Search by Mtsls1-BFGS for Continuous Global Optimization. GECCO (2015)
Jayadeva
Learning a hyperplane classifier by minimizing an exact bound on the VC dimension. Neurocomputing 149 (2015)
Jayadeva, Sanjit Singh Batra, Siddarth Sabharwal
Learning a Fuzzy Hyperplane Fat Margin Classifier with Minimum VC dimension. CoRR (2015)
Jayadeva, Sumit Soman, Amit Bhaya
The MC-ELM: Learning an ELM-like network with minimum VC dimension. IJCNN (2015)
Jayadeva, Sumit Soman, Amit Bhaya
A Neurodynamical System for finding a Minimal VC Dimension Classifier. CoRR (2015)
Phool Preet, Sanjit Singh Batra, Jayadeva
Feature Selection for classification of hyperspectral data by minimizing a tight bound on the VC dimension. CoRR (2015)
Udit Kumar, Jayadeva, Sumit Soman
Enhancing Incremental Ant Colony Algorithm for Continuous Global Optimization. GECCO (Companion) (2015)
Udit Kumar, Sumit Soman, Jayadeva
. CoRR (2015)
Jayadeva, Suresh Chandra, Siddarth Sabharwal, Sanjit S. Batra
Learning a hyperplane regressor by minimizing an exact bound on the VC dimension. CoRR (2014)
Eugenius Kaszkurewicz, Amit Bhaya, Jayadeva, João Marcos Meirelles da Silva
The Coupled EigenAnt algorithm for shortest path problems. IEEE Congress on Evolutionary Computation (2014)
Jayadeva
Learning a hyperplane classifier by minimizing an exact bound on the VC dimension. CoRR (2014)
Jayadeva, Sanjit S. Batra, Siddarth Sabharwal
Feature Selection through Minimization of the VC dimension. CoRR (2014)
Vasiliki N. Ikonomidou, Jayadeva, Robert W. Newcomb, Mona E. Zaghloul
Biomedical sensor properties of flexible PolyVinyliDene flouride. PETRA (2013)
Jayadeva, Sameena Shah, Amit Bhaya, Ravi Kothari, Suresh Chandra
Ants find the shortest path: a mathematical proof. Swarm Intell. 7 (1) (2013)
Audrey Tan, Dinesh K. Kumar, Sridhar P. Arjunan, Jayadeva
Computation and study of the low-frequency oscillation of surface electromyogram recorded in biceps during isometric upper limb contraction. EMBC (2013)
Sachindra Joshi, Jayadeva, Ganesh Ramakrishnan, Suresh Chandra
Using Sequential Unconstrained Minimization Techniques to simplify SVM solvers. Neurocomputing 77 (1) (2012)
Jayadeva, Sameena Shah, Ravi Kothari, Suresh Chandra
Debugging ants: How ants find the shortest route. ICICS (2011)
Sameena Shah, Jayadeva, Ravi Kothari, Suresh Chandra
M-Unit EigenAnt: An Ant Algorithm to Find the M Best Solutions. AAAI (2011)
Mittul Singh, Jivitej Chadha, Puneet Ahuja, Jayadeva, Suresh Chandra
Reduced twin support vector regression. Neurocomputing 74 (9) (2011)
Ganesh R. Naik, Dinesh Kant Kumar, Jayadeva
Twin SVM for gesture classification using the surface electromyogram. IEEE Trans. Inf. Technol. Biomed. 14 (2) (2010)
Sameena Shah, Ravi Kothari, Jayadeva, Suresh Chandra
Trail formation in ants. A generalized Polya urn process. Swarm Intell. 4 (2) (2010)
Reshma Khemchandani, Jayadeva, Suresh Chandra
Learning the optimal kernel for Fisher discriminant analysis via second order cone programming. Eur. J. Oper. Res. 203 (3) (2010)
Jayadeva, Sameena Shah, Suresh Chandra
Zero Norm Least Squares Proximal SVR. PReMI (2009)
Reshma Khemchandani, Jayadeva, Suresh Chandra
Regularized least squares fuzzy support vector regression for financial time series forecasting. Expert Syst. Appl. 36 (1) (2009)
Reshma Khemchandani, Jayadeva, Suresh Chandra
Optimal kernel selection in twin support vector machines. Optim. Lett. 3 (1) (2009)
Jayadeva, Sameena Shah, Suresh Chandra
Kernel Optimization Using a Generalized Eigenvalue Approach. PReMI (2009)
Reshma Khemchandani, Jayadeva, Suresh Chandra
Knowledge based proximal support vector machines. Eur. J. Oper. Res. 195 (3) (2009)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Regularized least squares support vector regression for the simultaneous learning of a function and its derivatives. Inf. Sci. 178 (17) (2008)
Reshma Khemchandani, Jayadeva, Suresh Chandra
Linear potential proximal support vector machines for pattern classification. Optim. Methods Softw. 23 (4) (2008)
V. Girish, Jayadeva, Saeid Nooshabadi
Design methodology for configurable analog to digital conversion using support vector machines. Microelectron. J. 39 (5) (2008)
Sameena Shah, Ravi Kothari, Jayadeva, Suresh Chandra
Mathematical Modeling and Convergence Analysis of Trail Formation. AAAI (2008)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Twin Support Vector Machines for Pattern Classification. IEEE Trans. Pattern Anal. Mach. Intell. 29 (5) (2007)
Alok Kanti Deb, Jayadeva, Madan Gopal, Suresh Chandra
SVM-Based Tree-Type Neural Networks as a Critic in Adaptive Critic Designs for Control. IEEE Trans. Neural Networks 18 (4) (2007)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Fuzzy multi-category proximal support vector classification via generalized eigenvalues. Soft Comput. 11 (7) (2007)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Regularized Least Squares Twin SVR for the Simultaneous Learning of a Function and its Derivative. IJCNN (2006)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Regularized Least Squares Fuzzy Support Vector Regression for Time Series Forecasting. IJCNN (2006)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Fuzzy Proximal Support Vector Classification Via Generalized Eigenvalues. PReMI (2005)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Fuzzy linear proximal support vector machines for multi-category data classification. Neurocomputing 67 (2005)
Jayadeva, Reshma Khemchandani, Suresh Chandra
Fast and robust learning through fuzzy linear proximal support vector machines. Neurocomputing 61 (2004)
Jayadeva, S. A. Rahman
A neural network with O(N) neurons for ranking N numbers in O(1/N) time. IEEE Trans. Circuits Syst. I Regul. Pap. (10) (2004)
Shantanu Chakrabartty, Gert Cauwenberghs, Jayadeva
Sparse Probability Regression by Label Partitioning. COLT (2003)
Jayadeva
Sequential Chaotic Annealing and its Application to Multilayer Channel Routing. VLSI Design (1999)
Jayadeva, Basabi Bhaumik
A neural network for the Steiner minimal tree problem. Biol. Cybern. 70 (5) (1994)
Jayadeva, Basabi Bhaumik
Optimization with neural networks: a recipe for improving convergence and solution quality. Biol. Cybern. 67 (5) (1992)