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2021

2023

2022

  • N. Tastan and K. Nandakumar, "CaPriDe Learning: Confidential and Private Decentralized Learning based on Encryption-friendly Distillation Loss", IEEE/CVF Conference on Computer Vision and Pattern Recognition Conference (CVPR), June 2023 (Accepted), pdf, code

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  • F. Shamshad, M. Nasser, and K. Nandakumar, "CLIP2Protect: Protecting Facial Privacy Using Makeup Text-Guided Adversarial Latent Search", IEEE/CVF Conference on Computer Vision and Pattern Recognition Conference (CVPR), June 2023 (Accepted), pdf

 

  • F. Shamshad, K. Srivatsan, and K. Nandakumar, "Evading Forensic Classifiers with Attribute-Conditioned Adversarial Faces", IEEE/CVF Conference on Computer Vision and Pattern Recognition Conference (CVPR), June 2023 (Accepted), pdf

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  • G. Kumar, S. Praveen, P. Kumar, M. Khapra, and K. Nandakumar, "Towards Building Text-To-Speech Systems for the Next Billion Users", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2023 (Accepted)

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  • M. Saeed, S. Nawaz, M. Khan, M. Zaheer, K. Nandakumar, M. Yousaf, and A. Mahmood, "Single-branch Network for Multimodal Training", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2023 (Accepted)

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  • T. Aremu and K. Nandakumar, “PolyKervNets: Activation-free Neural Networks For Efficient Private Inference”, IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), February 2023

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  • R. Alrefai and K. Nandakumar, “A Unified Model for Face Matching and Presentation Attack Detection Using an Ensemble of Vision Transformer Features“, Winter Conference on Applications of Computer Vision (WACV) Workshops, January 2023

 

  • S. Hashim, K. Nandakumar, and M. Yaqub, "Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer Data", Pacific Symposium on Biocomputing, January 2023

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  • G.K. Kumar and K. Nandakumar, “Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features“, Empirical Methods in Natural Language Processing (EMNLP) Workshops, December 2022

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  • O. Nazarov, M. Yaqub, and K. Nandakumar, “On the Importance of Image Encoding in Automated Chest X-Ray Report Generation”, British Machine Vision Conference (BMVC), November 2022

 

  • A. Godbole, K. Nandakumar, and A. K. Jain, "Learning an Ensemble of Deep Fingerprint Representations", arXiv preprint arXiv:2209.024252022

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  • A. Godbole, S.A. Grosz, K. Nandakumar, and A.K. Jain, “On Demographic Bias in Fingerprint Recognition”, International Joint Conference on Biometrics (IJCB), October 2022

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  • F. Almalik, M. Yaqub, and K. Nandakumar, “Self-Ensembling Vision Transformer (SEViT) for Robust Medical Image Classification”, 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), September 2022

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  • N. Alkhunaizi, D. Kamzolov, M. Takáč, and K. Nandakumar, “Suppressing Poisoning Attacks on Federated Learning for Medical Imaging”, 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), September 2022

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  • G.K. Kumar, A.S. Gehlot, S.S. Mullappilly, and K. Nandakumar, “MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages”, 2nd Workshop on Speech and Language Technologies for Dravidian Languages in conjunction with ACL 2022, May 2022

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  • S. Hashim, M. Ali, K. Nandakumar, and M. Yaqub, “SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification”, 10th International Conference on Bioinformatics and Computational Biology (ICBCB), May 2022

2021

  • K. Nandakumar, K. Sarpatwar, N. Ratha, S. Pankanti, R. Vaculin, K. Shanmugam, and J. Rayfield, "FHE-Friendly Distillation of Decision Tree Ensembles for Efficient Encrypted Inference", Third Privacy Preserving Machine Learning Workshop (PPML 2021), in conjunction with ACM CCS 2021, November 2021

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  • S. Srivastava, M. Yaqub, K. Nandakumar, Z. Ge, and D. Mahapatra, "Continual Domain Incremental Learning for Chest X-ray Classification in Low-Resource Clinical Settings", First Workshop on Affordable healthcare and AI for Resource diverse global health (FAIR-21), in conjunction with MICCAI 2021, September 2021.

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