Reshma Rastogi

According to our database, Reshma Rastogi authored at least 81 papers between 2004 and 2024.

Collaborative distances:

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

2024

Comprehensive review on twin support vector machines.

M. Tanveer, Taniya Rajani, Reshma Rastogi, Yuan-Hai Shao, M. A. Ganaie

Ann. Oper. Res., August, 2024

Parametric non-parallel support vector machines for pattern classification.

Sambhav Jain, Reshma Rastogi

Mach. Learn., April, 2024

Hypergraph Regularized Semi-supervised Least Squares Twin Support Vector Machine for Multilabel Classification.

Reshma Rastogi, Dev Nirwal

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Improved Hypergraph Laplacian Based Semi-supervised Support Vector Machine.

Reshma Rastogi, Dev Nirwal

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Adaptive Graph-Based Manifold Learning for Gene Selection.

Reshma Rastogi, Mamta Bhattarai Lamsal

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Binary-Tree Based Mean-Averaging Estimation for Multi-label Classification.

Reshma Rastogi, Sayanta Chowdhury

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Addressing Multi-Label Learning with Missing Labels via Feature Relevance guided Scaled Model Coefficients.

Sanjay Kumar, Reshma Rastogi

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Establishing Interconnections of Similarity-Based Classifiers for Multi-label Learning with Missing Labels.

Sambhav Jain, Reshma Rastogi

Proceedings of the Pattern Recognition - 27th International Conference, 2024

2023

Multi-label learning with missing labels using sparse global structure for label-specific features.

Sanjay Kumar, Nadira Ahmadi, Reshma Rastogi

Appl. Intell., August, 2023

Discriminatory Label-specific Weights for Multi-label Learning with Missing Labels.

Reshma Rastogi, Sanjay Kumar

Neural Process. Lett., April, 2023

Time efficient variants of Twin Extreme Learning Machine.

Pritam Anand, Amisha Bharti, Reshma Rastogi

Intell. Syst. Appl., 2023

2022

Low rank label subspace transformation for multi-label learning with missing labels.

Sanjay Kumar, Reshma Rastogi

Inf. Sci., 2022

Imbalance multi-label data learning with label specific features.

Reshma Rastogi, Sayed Mortaza

Neurocomputing, 2022

Multi-label learning via minimax probability machine.

Reshma Rastogi, Sambhav Jain

Int. J. Approx. Reason., 2022

Auxiliary Label Embedding for Multi-label Learning with Missing Labels.

Sanjay Kumar, Reshma Rastogi

Proceedings of the Computer Vision and Machine Intelligence, 2022

2021

Large-Scale Twin Parametric Support Vector Machine Using Pinball Loss Function.

Sweta Sharma, Reshma Rastogi, Suresh Chandra

IEEE Trans. Syst. Man Cybern. Syst., 2021

Ternary tree-based structural twin support tensor machine for clustering.

Reshma Rastogi, Sweta Sharma

Pattern Anal. Appl., 2021

Multi-label classification with Missing Labels using Label Correlation and Robust Structural Learning.

Reshma Rastogi, Sayed Mortaza

Knowl. Based Syst., 2021

Sparse support vector machine with pinball loss.

Mohammad Tanveer, Sweta Sharma, Reshma Rastogi, Pritam Anand

Trans. Emerg. Telecommun. Technol., 2021

Efficient Learning of Pinball TWSVM using Privileged Information and its applications.

Reshma Rastogi, Aman Pal

CoRR, 2021

Improvement over Pinball Loss Support Vector Machine.

Pritam Anand, Reshma Rastogi, Suresh Chandra

CoRR, 2021

Comprehensive Review On Twin Support Vector Machines.

Mohammad Tanveer, Taniya Rajani, Reshma Rastogi, Yuan-Hai Shao

CoRR, 2021

Stochastic Quasi-Newton Minimum Complexity Machine for Pattern Classification.

Reshma Rastogi, Sweta Sharma, Suresh Chandra

Proceedings of the Pattern Recognition and Machine Intelligence, 2021

2020

Semi-supervised Weighted Ternary Decision Structure for Multi-category Classification.

Pooja Saigal, Reshma Rastogi, Suresh Chandra

Neural Process. Lett., 2020

Large-margin Distribution Machine-based regression.

Reshma Rastogi, Pritam Anand, Suresh Chandra

Neural Comput. Appl., 2020

Nonparallel Hyperplane Classifiers for Multi-category Classification.

Pooja Saigal, Reshma Khemchandani

CoRR, 2020

A new asymmetric ϵ-insensitive pinball loss function based support vector quantile regression model.

Pritam Anand, Reshma Rastogi, Suresh Chandra

Appl. Soft Comput., 2020

A class of new Support Vector Regression models.

Pritam Anand, Reshma Rastogi, Suresh Chandra

Appl. Soft Comput., 2020

2019

Fuzzy semi-supervised weighted linear loss twin support vector clustering.

Reshma Rastogi, Aman Pal

Knowl. Based Syst., 2019

Multi-category ternion support vector machine.

Pooja Saigal, Suresh Chandra, Reshma Rastogi

Eng. Appl. Artif. Intell., 2019

A ν-support vector quantile regression model with automatic accuracy control.

Pritam Anand, Reshma Rastogi, Suresh Chandra

CoRR, 2019

Support Vector Regression via a Combined Reward Cum Penalty Loss Function.

Pritam Anand, Reshma Rastogi, Suresh Chandra

CoRR, 2019

Fast Laplacian twin support vector machine with active learning for pattern classification.

Reshma Rastogi, Sweta Sharma

Appl. Soft Comput., 2019

Semi-supervised Multi-category Classification with Generative Adversarial Networks.

Reshma Rastogi, Ritesh Gangnani

Proceedings of the Pattern Recognition and Machine Intelligence, 2019

A Unified Multi-label Relationship Learning.

Reshma Rastogi, Simran Popli, Nima Dorji Moktan, Sweta Sharma

Proceedings of the 14th International Conference on Computer Science & Education, 2019

2018

Robust Parametric Twin Support Vector Machine for Pattern Classification.

Reshma Rastogi, Sweta Sharma, Suresh Chandra

Neural Process. Lett., 2018

Fuzzy least squares twin support vector clustering.

Reshma Khemchandani, Aman Pal, Suresh Chandra

Neural Comput. Appl., 2018

Generalized eigenvalue proximal support vector regressor for the simultaneous learning of a function and its derivatives.

Reshma Khemchandani, Keshav Goyal, Suresh Chandra

Int. J. Mach. Learn. Cybern., 2018

Angle-based twin parametric-margin support vector machine for pattern classification.

Reshma Rastogi, Pooja Saigal, Suresh Chandra

Knowl. Based Syst., 2018

Generalized Pinball Loss SVMs.

Reshma Rastogi, Aman Pal, Suresh Chandra

Neurocomputing, 2018

Angle-based twin support vector machine.

Reshma Khemchandani, Pooja Saigal, Suresh Chandra

Ann. Oper. Res., 2018

Maximum Margin Minimum Variance Twin Support Vector Machine.

Sweta Sharma, Reshma Rastogi

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Insensitive Zone based Pinball Loss Twin Support Vector Machine for Pattern Classification.

Sweta Sharma, Reshma Rastogi

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Exploring Data Reduction Techniques for Time Efficient Support Vector Machine Classifiers.

Reshma Rastogi, Hamid Safdari, Sweta Sharma

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Learning TWSVM using Privilege Information.

Aman Pal, Reshma Rastogi

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Self-Attention Enhanced Recurrent Neural Networks for Sentence Classification.

Ankit Kumar, Reshma Rastogi

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

A Pinball loss based Extreme Learning Machine for pattern classification.

Pritam Anand, Reshma Rastogi, Amisha Bharti

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Stochastic Conjugate Gradient Descent Twin Support Vector Machine for Large Scale Pattern Classification.

Sweta Sharma, Reshma Rastogi

Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018

2017

Twin Support Vector Machines - Models, Extensions and Applications

Jayadeva, Reshma Khemchandani, Suresh Chandra

Studies in Computational Intelligence 659, Springer, ISBN: 978-3-319-46186-1, 2017

Tree based multi-category Laplacian TWSVM for content based image retrieval.

Reshma Khemchandani, Aman Pal

Int. J. Mach. Learn. Cybern., 2017

Divide and conquer approach for semi-supervised multi-category classification through localized kernel spectral clustering.

Pooja Saigal, Vaibhav Khanna, Reshma Rastogi

Neurocomputing, 2017

Tree-based localized fuzzy twin support vector clustering with square loss function.

Reshma Rastogi, Pooja Saigal

Appl. Intell., 2017

A ν-twin support vector machine based regression with automatic accuracy control.

Reshma Rastogi, Pritam Anand, Suresh Chandra

Appl. Intell., 2017

Tree-Based Structural Twin Support Tensor Clustering with Square Loss Function.

Reshma Rastogi, Sweta Sharma

Proceedings of the Pattern Recognition and Machine Intelligence, 2017

2016

Improvements on ν-Twin Support Vector Machine.

Reshma Khemchandani, Pooja Saigal, Suresh Chandra

Neural Networks, 2016

TWSVR: Regression via Twin Support Vector Machine.

Reshma Khemchandani, Keshav Goyal, Suresh Chandra

Neural Networks, 2016

Robust least squares twin support vector machine for human activity recognition.

Reshma Khemchandani, Sweta Sharma

Appl. Soft Comput., 2016

Multi-category laplacian least squares twin support vector machine.

Reshma Khemchandani, Aman Pal

Appl. Intell., 2016

Single asset optimal trading strategies with stochastic dominance constraints.

Reshma Khemchandani, Avikant Bhardwaj, Suresh Chandra

Ann. Oper. Res., 2016

Robust Parametric Twin Support Vector Machine and Its Application in Human Activity Recognition.

Reshma Khemchandani, Sweta Sharma

Proceedings of International Conference on Computer Vision and Image Processing, 2016

Weighted Linear Loss Twin Support Vector Clustering.

Reshma Khemchandani, Aman Pal

Proceedings of the 3rd IKDD Conference on Data Science, 2016

2015

Color image classification and retrieval through ternary decision structure based multi-category TWSVM.

Reshma Khemchandani, Pooja Saigal

Neurocomputing, 2015

Twin Support Vector Machine based Regression.

Reshma Khemchandani, Keshav Goyal, Suresh Chandra

Proceedings of the Eighth International Conference on Advances in Pattern Recognition, 2015

2013

Optimal execution with weighted impact functions: a quadratic programming approach.

Reshma Khemchandani, Nishil Gupta, Arpit Chaudhary, Suresh Chandra

Optim. Lett., 2013

Proximal support tensor machines.

Reshma Khemchandani, Anuj Karpatne, Suresh Chandra

Int. J. Mach. Learn. Cybern., 2013

Twin support vector regression for the simultaneous learning of a function and its derivatives.

Reshma Khemchandani, Anuj Karpatne, Suresh Chandra

Int. J. Mach. Learn. Cybern., 2013

2011

Generalized eigenvalue proximal support vector regressor.

Reshma Khemchandani, Anuj Karpatne, Suresh Chandra

Expert Syst. Appl., 2011

2010

Knowledge based Least Squares Twin support vector machines.

M. Arun Kumar, Reshma Khemchandani, Madan Gopal, Suresh Chandra

Inf. Sci., 2010

Learning the optimal kernel for Fisher discriminant analysis via second order cone programming.

Reshma Khemchandani, Jayadeva, Suresh Chandra

Eur. J. Oper. Res., 2010

2009

Optimal kernel selection in twin support vector machines.

Reshma Khemchandani, Jayadeva, Suresh Chandra

Optim. Lett., 2009

Regularized least squares fuzzy support vector regression for financial time series forecasting.

Reshma Khemchandani, Jayadeva, Suresh Chandra

Expert Syst. Appl., 2009

Knowledge based proximal support vector machines.

Reshma Khemchandani, Jayadeva, Suresh Chandra

Eur. J. Oper. Res., 2009

2008

Linear potential proximal support vector machines for pattern classification.

Reshma Khemchandani, Jayadeva, Suresh Chandra

Optim. Methods Softw., 2008

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

Jayadeva, Reshma Khemchandani, Suresh Chandra

Inf. Sci., 2008

2007

Fuzzy multi-category proximal support vector classification via generalized eigenvalues.

Jayadeva, Reshma Khemchandani, Suresh Chandra

Soft Comput., 2007

Twin Support Vector Machines for Pattern Classification.

Jayadeva, Reshma Khemchandani, Suresh Chandra

IEEE Trans. Pattern Anal. Mach. Intell., 2007

2006

Regularized Least Squares Twin SVR for the Simultaneous Learning of a Function and its Derivative.

Jayadeva, Reshma Khemchandani, Suresh Chandra

Proceedings of the International Joint Conference on Neural Networks, 2006

Regularized Least Squares Fuzzy Support Vector Regression for Time Series Forecasting.

Jayadeva, Reshma Khemchandani, Suresh Chandra

Proceedings of the International Joint Conference on Neural Networks, 2006

2005

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

Jayadeva, Reshma Khemchandani, Suresh Chandra

Neurocomputing, 2005

Fuzzy Proximal Support Vector Classification Via Generalized Eigenvalues.

Jayadeva, Reshma Khemchandani, Suresh Chandra

Proceedings of the Pattern Recognition and Machine Intelligence, 2005

2004

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

Jayadeva, Reshma Khemchandani, Suresh Chandra

Neurocomputing, 2004