| Recent advances in differential evolution–an updated survey. S Das, SS Mullick, PN Suganthan Swarm and Evolutionary Computation 27, 1-30, 2016 | 1707 | 2016 |
| Generative adversarial minority oversampling SS Mullick, S Datta, S Das Proceedings of the IEEE International Conference on Computer Vision, 1695-1704, 2019 | 254 | 2019 |
| Adaptive Learning-Based -Nearest Neighbor Classifiers With Resilience to Class Imbalance SS Mullick, S Datta, S Das IEEE transactions on neural networks and learning systems 29 (11), 5713-5725, 2018 | 127 | 2018 |
| Appropriateness of performance indices for imbalanced data classification: An analysis SS Mullick, S Datta, SG Dhekane, S Das Pattern Recognition 102, 107197, 2020 | 80 | 2020 |
| On supervised class-imbalanced learning: An updated perspective and some key challenges S Das, SS Mullick, I Zelinka IEEE Transactions on Artificial Intelligence 3 (6), 973-993, 2022 | 63 | 2022 |
| A parameter independent fuzzy weighted k-nearest neighbor classifier N Biswas, S Chakraborty, SS Mullick, S Das Pattern Recognition Letters 101, 80-87, 2018 | 61 | 2018 |
| A switched parameter differential evolution with optional blending crossover for scalable numerical optimization A Ghosh, S Das, SS Mullick, R Mallipeddi, AK Das Applied Soft Computing 57, 329-352, 2017 | 48 | 2017 |
| A black-box adversarial attack strategy with adjustable sparsity and generalizability for deep image classifiers A Ghosh, SS Mullick, S Datta, S Das, AK Das, R Mallipeddi Pattern Recognition 122, 108279, 2022 | 35 | 2022 |
| A switched parameter differential evolution for large scale global optimization–simpler may be better S Das, A Ghosh, SS Mullick Mendel 2015: Recent Advances in Soft Computing, 103-125, 2015 | 27 | 2015 |
| On Convergence of the Class Membership Estimator in Fuzzy -Nearest Neighbor Classifier I Banerjee, SS Mullick, S Das IEEE Transactions on Fuzzy Systems 27 (6), 1226-1236, 2018 | 16 | 2018 |
| Content moderation for evolving policies using binary question answering SS Mullick, M Bhambhani, S Sinha, A Mathur, S Gupta, J Shah Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 10 | 2023 |
| Do preprocessing and class imbalance matter to the deep image classifiers for COVID-19 detection? An explainable analysis A Basu, S Das, SS Mullick, S Das IEEE Transactions on Artificial Intelligence 4 (2), 229-241, 2022 | 10 | 2022 |
| Diversifying support vector machines for boosting using kernel perturbation: Applications to class imbalance and small disjuncts S Datta, S Nag, SS Mullick, S Das arXiv preprint arXiv:1712.08493, 2017 | 6 | 2017 |
| Interval Bound Interpolation for Few-shot Learning with Few Tasks S Datta, SS Mullick, A Chakrabarty, S Das International Conference on Machine Learning, 7141-7166, 2023 | 4 | 2023 |
| Generalized mean based back-propagation of errors for ambiguity resolution S Datta, SS Mullick, S Das Pattern Recognition Letters 94, 22-29, 2017 | 1 | 2017 |
| Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures A Basu, K Bose, SS Mullick, A Chakrabarty, S Das arXiv preprint arXiv:2404.06294, 2024 | | 2024 |
| On Class Imbalanced Learning: Design of Non-parametricClassifiers, Performance Indices, and Deep Oversampling Strategies SS Mullick Indian Statistical Institute, 2021 | | 2021 |
| Enhancing Contrastive Clustering with Negative Pair-guided Regularization A Kumar, A Chakrabarty, SS Mullick, S Das Transactions on Machine Learning Research, 0 | | |
Swagatam DasProfessor, Electronics and Communication Sciences Unit, Indian Statistical Institute, KolkataVerified email at isical.ac.in
