Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift.
CoRR, 2023
Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Multi-Variate Time Series Forecasting on Variable Subsets.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Compact Feature Representation for Unsupervised Ood Detection.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
Domain-Agnostic Contrastive Representations for Learning from Label Proportions.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Adversarially Robust Classifier with Covariate Shift Adaptation.
CoRR, 2021
Distributional Shifts In Automated Diabetic Retinopathy Screening.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Approximate Manifold Defense Against Multiple Adversarial Perturbations.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Normal Similarity Network for Generative Modelling.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018
An Incremental Feature Extraction Framework for Referable Diabetic Retinopathy Detection.
Proceedings of the 28th IEEE International Conference on Tools with Artificial Intelligence, 2016