Hybrid Unsupervised and Supervised Multitask Learning For Speech Recognition in Low Resource Languages
K.M Srinivasa Raghavan, Kumar Shubham
Workshop on Machine Learning in Speech and Language Processing(MLSLP), Interspeech. 2021.
Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation
Kumar Shubham, Gopalakrishnan Venkatesh, Reijul Sachdev, Akshi, Dinesh Babu Jayagopi, G. Srinivasaraghavan
International Joint Conference on Neural Network(IJCNN) . 2021.
Conventional and Non-conventional Job Interviewing Methods: A Comparative Study in Two Countries
Kumar Shubham, Emmanuelle Patricia Kleinlogel, Anaïs Butera, Marianne Schmid Mast Dinesh Babu Jayagopi
Conference : International Conference on Multimodal Interaction(ICMI). 2020.
A regularization on Lagrangian twin support vector regression
Muhammad Tanveer, Kumar Shubham
Journal : International Journal of Machine Learning and Cybernetics. 2017. impact factor : 4.08 (2018).
Smooth twin support vector machines via unconstrained convex minimization
Muhammad Tanveer, Kumar Shubham
Journal : Filomat. 2017. impact factor : 0.76 (2019).
An efficient regularized K-nearest neighbor based weighted twin support vector regression
Muhammad Tanveer, Kumar Shubham, Mujahed Aldhaifallah, SS Ho
Journal : Knowledge-Based Systems. 2016. impact factor : 5.101 (2018).
An efficient implicit regularized Lagrangian twin support vector regression
Muhammad Tanveer, Kumar Shubham, Mujahed Aldhaifallah, KS Nisar
Journal : Applied intelligence . 2016. impact factor : 0.988 (2018).