Jayadeva - RankMe

105 papers A* 8A 1B 12C 1Misc 1Journal 70Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Leap of FAITH from GNN-to-MLP: Fairness Aware Inference via DisTillation of GrapH Knowledge. AAAI Vipul Kumar Singh, Jyotismita Barman, Sandeep Kumar, Tapan K. Gandhi, Jayadeva
2025	J	`jnl`	A Unified Optimization-Based Framework for Certifiably Robust and Fair Graph Neural Networks. IEEE Trans. Signal Process. Vipul Kumar Singh, Sandeep Kumar, Avadhesh Prasad, Jayadeva
2025	J	`jnl`	A novel coarsened graph learning method for scalable single-cell data analysis. Comput. Biol. Medicine Mohit Kataria, Ekta Srivastava, Kumar Arjun, Sandeep Kumar, Ishaan Gupta, Jayadeva
2025	J	`jnl`	AH-UGC: Adaptive and Heterogeneous-Universal Graph Coarsening. CoRR Mohit Kataria, Shreyash Bhilwade, Sandeep Kumar, Jayadeva
2025	J	`jnl`	GraphFLEx: Structure Learning Framework for Large Expanding Graphs. CoRR Mohit Kataria, Nikita Malik, Sandeep Kumar, Jayadeva
2025	J	`jnl`	On the Equivalence of Regression and Classification. CoRR Jayadeva, Naman Dwivedi, Hari Krishnan, N. M. Anoop Krishnan
2025	B	`conf`	REFINE: Enabling Efficient and Trustworthy Modeling of Financial Networks via GNN-to-MLP Knowledge Distillation. DSAA Vipul Kumar Singh, Jyotismita Barman, Sandeep Kumar, Jayadeva
2024	A*	`conf`	BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics. ICLR Suresh Bishnoi, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
2024	—	`conf`	CoRE-BOLD: Cross-Domain Robust and Equitable Ensemble for BOLD Signal Analysis. ML4H@NeurIPS Vipul Kumar Singh, Jyotismita Barman, Sandeep Kumar, Jayadeva
2024	J	`jnl`	Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks. Mach. Learn. Sci. Technol. Suresh Bishnoi, Ravinder Bhattoo, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
2024	B	`conf`	HybMT: Hybrid Meta-Predictor based ML Algorithm for Fast Test Vector Generation. ASPDAC Shruti Pandey, Jayadeva, Smruti R. Sarangi
2024	A*	`conf`	No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation. AAAI Nimesh Agrawal, Anuj Kumar Sirohi, Sandeep Kumar, Jayadeva
2024	A*	`conf`	UGC: Universal Graph Coarsening. NeurIPS Mohit Kataria, Sandeep Kumar, Jayadeva
2023	J	`jnl`	Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks. CoRR Suresh Bishnoi, Ravinder Bhattoo, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
2023	A*	`conf`	Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems. ICLR Suresh Bishnoi, Ravinder Bhattoo, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
2023	J	`jnl`	Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics. CoRR Suresh Bishnoi, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
2023	J	`jnl`	MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models. CoRR Mohd Zaki, Jayadeva, Mausam, N. M. Anoop Krishnan
2023	J	`jnl`	Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas. IEEE Access Debanjali Sarkar, Taimoor Khan, Jayadeva, Ahmed A. Kishk
2023	J	`jnl`	No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation. CoRR Nimesh Agrawal, Anuj Kumar Sirohi, Jayadeva, Sandeep Kumar
2022	J	`jnl`	A Novel Meta-predictor based Algorithm for Testing VLSI Circuits. CoRR Shruti Pandey, Jayadeva, Smruti R. Sarangi
2022	J	`jnl`	Block Sparse Variational Bayes Regression Using Matrix Variate Distributions With Application to SSVEP Detection. IEEE Trans. Neural Networks Learn. Syst. Shruti Sharma, Santanu Chaudhury, Jayadeva
2022	J	`jnl`	Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images. CoRR Mohd Zaki, Siddhant Sharma, Sunil Kumar Gurjar, Raju Goyal, Jayadeva, N. M. Anoop Krishnan
2022	J	`jnl`	Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors. CoRR Suresh Bishnoi, Skyler Badge, Jayadeva, N. M. Anoop Krishnan
2021	J	`jnl`	ComBI: Compressed Binary Search Tree for Approximate Big Data Res. Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
2021	B	`conf`	Enhash: A Fast Streaming Algorithm For Concept Drift Detection. ESANN Aashi Jindal, Prashant Gupta, Debarka Sengupta, Jayadeva
2021	J	`jnl`	Kernel optimization using conformal maps for the minimal complexity machine. Eng. Appl. Artif. Intell. Skyler Badge, Sumit Soman, Suresh Chandra, Jayadeva
2021	J	`jnl`	Linear time identification of local and global outliers. Neurocomputing Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
2021	J	`jnl`	Minimal Complexity Machines Under Weight Quantization. IEEE Trans. Computers Mayank Sharma, Sumit Soman, Jayadeva
2021	J	`jnl`	Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images. CoRR Kartikeya Badola, Sameer Ambekar, Himanshu Pant, Sumit Soman, Anuradha Sural, Rajiv Narang, Suresh Chandra, Jayadeva
2020	J	`jnl`	Complexity Controlled Generative Adversarial Networks. CoRR Himanshu Pant, Jayadeva, Sumit Soman
2020	J	`jnl`	Enhash: A Fast Streaming Algorithm For Concept Drift Detection. CoRR Aashi Jindal, Prashant Gupta, Debarka Sengupta, Jayadeva
2020	J	`jnl`	Neurodynamical classifiers with low model complexity. Neural Networks Himanshu Pant, Sumit Soman, Jayadeva, Amit Bhaya
2020	J	`jnl`	QMCM: Minimizing Vapnik's bound on the VC dimension. Neurocomputing Jayadeva, Sumit Soman, Himanshu Pant, Mayank Sharma
2020	J	`jnl`	Sparsity in function and derivative approximation via the empirical feature space. Inf. Sci. Sumit Soman, Jayadeva, Rajat Thakur, Mayank Sharma, Suresh Chandra
2019	J	`jnl`	Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise. CoRR Mayank Sharma, Aayush Yadav, Sumit Soman, Jayadeva
2019	J	`jnl`	Guided Random Forest and its application to data approximation. CoRR Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
2019	—	`conf`	Learning from Low Training Data using Classifiers with Derivative Constraints. COMAD/CODS Sumit Soman, Jayadeva
2019	J	`jnl`	Smaller Models, Better Generalization. CoRR Mayank Sharma, Suraj Tripathi, Abhimanyu Dubey, Jayadeva, Sai Guruju, Nihal Goalla
2019	J	`jnl`	Twin Neural Networks for the classification of large unbalanced datasets. Neurocomputing Jayadeva, Himanshu Pant, Mayank Sharma, Sumit Soman
2018	J	`jnl`	Eigen-MM: EigenAnt Modified Mtsls1 for local search. Swarm Evol. Comput. Udit Kumar, Sumit Soman, Jayadeva
2018	J	`jnl`	EigenSample: A non-iterative technique for adding samples to small datasets. Appl. Soft Comput. Jayadeva, Sumit Soman, Soumya Saxena
2018	B	`conf`	Non-Mercer Large Scale Multiclass Least Squares Minimal Complexity Machines. IJCNN Mayank Sharma, Sumit Soman, Jayadeva, Himanshu Pant
2018	J	`jnl`	Radius-margin bounds for deep neural networks. CoRR Mayank Sharma, Jayadeva, Sumit Soman
2018	—	`conf`	Some Comments on Variational Bayes Block Sparse Modeling with Correlated Entries. RRPR Shruti Sharma, Santanu Chaudhury, Jayadeva
2018	—	`conf`	Sparse Signal Recovery for Multiple Measurement Vectors with Temporally Correlated Entries: A Bayesian Perspective. ICVGIP Shruti Sharma, Santanu Chaudhury, Jayadeva, Snigdha Bhagat
2018	—	`conf`	Temporal Modeling of EEG Signals using Block Sparse Variational Bayes Framework. ICVGIP Shruti Sharma, Santanu Chaudhury, Jayadeva
2018	B	`conf`	Twin Neural Networks for Efficient EEG Signal Classification. IJCNN Himanshu Pant, Sumit Soman, Jayadeva, Mayank Sharma
2018	J	`jnl`	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. Jayadeva, Mayank Sharma, Sumit Soman, Himanshu Pant
2018	B	`conf`	Variational Bayes Block Sparse Modeling with Correlated Entries. ICPR Shruti Sharma, Santanu Chaudhury, Jayadeva
2017	J	`jnl`	A Data and Model-Parallel, Distributed and Scalable Framework for Training of Deep Networks in Apache Spark. CoRR Disha Shrivastava, Santanu Chaudhury, Jayadeva
2017	J	`jnl`	Large-Scale Minimal Complexity Machines Using Explicit Feature Maps. IEEE Trans. Syst. Man Cybern. Syst. Mayank Sharma, Jayadeva, Sumit Soman, Himanshu Pant
2017	J	`jnl`	Learning Neural Network Classifiers with Low Model Complexity. CoRR Jayadeva, Himanshu Pant, Mayank Sharma, Abhimanyu Dubey, Sumit Soman, Sai Guruju, Nihal Goalla
2017	J	`jnl`	Scalable Twin Neural Networks for Classification of Unbalanced Data. CoRR Himanshu Pant, Jayadeva, Sumit Soman, Mayank Sharma
2017	J	`jnl`	Sparse short-term time series forecasting models via minimum model complexity. Neurocomputing Pawas Gupta, Sanjit S. Batra, Jayadeva
2017	—	`book`	Twin Support Vector Machines - Models, Extensions and Applications Jayadeva, Reshma Khemchandani, Suresh Chandra
2016	J	`jnl`	Benchmarking NLopt and state-of-the-art algorithms for continuous global optimization via Swarm Evol. Comput. Udit Kumar, Sumit Soman, Jayadeva
2016	B	`conf`	EigenAnt assisted IACOℝ for continuous global optimization. SMC Udit Kumar, Sumit Soman, Jayadeva
2016	J	`jnl`	Examining Representational Similarity in ConvNets and the Primate Visual Cortex. CoRR Abhimanyu Dubey, Jayadeva, Sumeet Agarwal
2016	B	`conf`	Improved sEMG signal classification using the Twin SVM. SMC Sumit Soman, Jayadeva, Sridhar P. Arjunan, Dinesh Kant Kumar
2016	J	`jnl`	Learning a hyperplane regressor through a tight bound on the VC dimension. Neurocomputing Jayadeva, Suresh Chandra, Sanjit S. Batra, Siddarth Sabharwal
2015	J	`jnl`	A Neurodynamical System for finding a Minimal VC Dimension Classifier. CoRR Jayadeva, Sumit Soman, Amit Bhaya
2015	J	`jnl`	Benchmarking NLopt and state-of-art algorithms for Continuous Global Optimization via Hybrid IACO CoRR Udit Kumar, Sumit Soman, Jayadeva
2015	A	`conf`	Enhancing IACO GECCO Udit Kumar, Jayadeva, Sumit Soman
2015	—	`conf`	Enhancing Incremental Ant Colony Algorithm for Continuous Global Optimization. GECCO (Companion) Udit Kumar, Jayadeva, Sumit Soman
2015	J	`jnl`	Feature Selection for classification of hyperspectral data by minimizing a tight bound on the VC dimension. CoRR Phool Preet, Sanjit Singh Batra, Jayadeva
2015	J	`jnl`	High performance EEG signal classification using classifiability and the Twin SVM. Appl. Soft Comput. Sumit Soman, Jayadeva
2015	J	`jnl`	Learning a Fuzzy Hyperplane Fat Margin Classifier with Minimum VC dimension. CoRR Jayadeva, Sanjit Singh Batra, Siddarth Sabharwal
2015	J	`jnl`	Learning a hyperplane classifier by minimizing an exact bound on the VC dimension. Neurocomputing Jayadeva
2015	B	`conf`	The MC-ELM: Learning an ELM-like network with minimum VC dimension. IJCNN Jayadeva, Sumit Soman, Amit Bhaya
2014	J	`jnl`	Feature Selection through Minimization of the VC dimension. CoRR Jayadeva, Sanjit S. Batra, Siddarth Sabharwal
2014	J	`jnl`	Learning a hyperplane classifier by minimizing an exact bound on the VC dimension. CoRR Jayadeva
2014	J	`jnl`	Learning a hyperplane regressor by minimizing an exact bound on the VC dimension. CoRR Jayadeva, Suresh Chandra, Siddarth Sabharwal, Sanjit S. Batra
2014	B	`conf`	The Coupled EigenAnt algorithm for shortest path problems. IEEE Congress on Evolutionary Computation Eugenius Kaszkurewicz, Amit Bhaya, Jayadeva, João Marcos Meirelles da Silva
2013	J	`jnl`	Ants find the shortest path: a mathematical proof. Swarm Intell. Jayadeva, Sameena Shah, Amit Bhaya, Ravi Kothari, Suresh Chandra
2013	—	`conf`	Biomedical sensor properties of flexible PolyVinyliDene flouride. PETRA Vasiliki N. Ikonomidou, Jayadeva, Robert W. Newcomb, Mona E. Zaghloul
2013	—	`conf`	Computation and study of the low-frequency oscillation of surface electromyogram recorded in biceps during isometric upper limb contraction. EMBC Audrey Tan, Dinesh K. Kumar, Sridhar P. Arjunan, Jayadeva
2012	J	`jnl`	Using Sequential Unconstrained Minimization Techniques to simplify SVM solvers. Neurocomputing Sachindra Joshi, Jayadeva, Ganesh Ramakrishnan, Suresh Chandra
2011	C	`conf`	Debugging ants: How ants find the shortest route. ICICS Jayadeva, Sameena Shah, Ravi Kothari, Suresh Chandra
2011	A*	`conf`	M-Unit EigenAnt: An Ant Algorithm to Find the M Best Solutions. AAAI Sameena Shah, Jayadeva, Ravi Kothari, Suresh Chandra
2011	J	`jnl`	Reduced twin support vector regression. Neurocomputing Mittul Singh, Jivitej Chadha, Puneet Ahuja, Jayadeva, Suresh Chandra
2010	J	`jnl`	Learning the optimal kernel for Fisher discriminant analysis via second order cone programming. Eur. J. Oper. Res. Reshma Khemchandani, Jayadeva, Suresh Chandra
2010	J	`jnl`	Trail formation in ants. A generalized Polya urn process. Swarm Intell. Sameena Shah, Ravi Kothari, Jayadeva, Suresh Chandra
2010	J	`jnl`	Twin SVM for gesture classification using the surface electromyogram. IEEE Trans. Inf. Technol. Biomed. Ganesh R. Naik, Dinesh Kant Kumar, Jayadeva
2009	—	`conf`	Kernel Optimization Using a Generalized Eigenvalue Approach. PReMI Jayadeva, Sameena Shah, Suresh Chandra
2009	J	`jnl`	Knowledge based proximal support vector machines. Eur. J. Oper. Res. Reshma Khemchandani, Jayadeva, Suresh Chandra
2009	J	`jnl`	Optimal kernel selection in twin support vector machines. Optim. Lett. Reshma Khemchandani, Jayadeva, Suresh Chandra
2009	J	`jnl`	Regularized least squares fuzzy support vector regression for financial time series forecasting. Expert Syst. Appl. Reshma Khemchandani, Jayadeva, Suresh Chandra
2009	—	`conf`	Zero Norm Least Squares Proximal SVR. PReMI Jayadeva, Sameena Shah, Suresh Chandra
2008	J	`jnl`	Design methodology for configurable analog to digital conversion using support vector machines. Microelectron. J. V. Girish, Jayadeva, Saeid Nooshabadi
2008	J	`jnl`	Linear potential proximal support vector machines for pattern classification. Optim. Methods Softw. Reshma Khemchandani, Jayadeva, Suresh Chandra
2008	A*	`conf`	Mathematical Modeling and Convergence Analysis of Trail Formation. AAAI Sameena Shah, Ravi Kothari, Jayadeva, Suresh Chandra
2008	J	`jnl`	Regularized least squares support vector regression for the simultaneous learning of a function and its derivatives. Inf. Sci. Jayadeva, Reshma Khemchandani, Suresh Chandra
2007	J	`jnl`	Fuzzy multi-category proximal support vector classification via generalized eigenvalues. Soft Comput. Jayadeva, Reshma Khemchandani, Suresh Chandra
2007	J	`jnl`	SVM-Based Tree-Type Neural Networks as a Critic in Adaptive Critic Designs for Control. IEEE Trans. Neural Networks Alok Kanti Deb, Jayadeva, Madan Gopal, Suresh Chandra
2007	J	`jnl`	Twin Support Vector Machines for Pattern Classification. IEEE Trans. Pattern Anal. Mach. Intell. Jayadeva, Reshma Khemchandani, Suresh Chandra
2006	B	`conf`	Regularized Least Squares Fuzzy Support Vector Regression for Time Series Forecasting. IJCNN Jayadeva, Reshma Khemchandani, Suresh Chandra
2006	B	`conf`	Regularized Least Squares Twin SVR for the Simultaneous Learning of a Function and its Derivative. IJCNN Jayadeva, Reshma Khemchandani, Suresh Chandra
2005	—	`conf`	Fuzzy Proximal Support Vector Classification Via Generalized Eigenvalues. PReMI Jayadeva, Reshma Khemchandani, Suresh Chandra
2005	J	`jnl`	Fuzzy linear proximal support vector machines for multi-category data classification. Neurocomputing Jayadeva, Reshma Khemchandani, Suresh Chandra
2004	J	`jnl`	A neural network with O(N) neurons for ranking N numbers in O(1/N) time. IEEE Trans. Circuits Syst. I Regul. Pap. Jayadeva, Syed Atiqur Rahman
2004	J	`jnl`	Fast and robust learning through fuzzy linear proximal support vector machines. Neurocomputing Jayadeva, Reshma Khemchandani, Suresh Chandra
2003	A*	`conf`	Sparse Probability Regression by Label Partitioning. COLT Shantanu Chakrabartty, Gert Cauwenberghs, Jayadeva
1999	Misc	`conf`	Sequential Chaotic Annealing and its Application to Multilayer Channel Routing. VLSI Design Jayadeva
1994	J	`jnl`	A neural network for the Steiner minimal tree problem. Biol. Cybern. Jayadeva, Basabi Bhaumik
1992	J	`jnl`	Optimization with neural networks: a recipe for improving convergence and solution quality. Biol. Cybern. Jayadeva, Basabi Bhaumik