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cs.LG2024
MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection
Niki Nezakati, Md Kaykobad Reza, Ameya Patil +2
Multimodal learning seeks to combine data from multiple input sources to enhance the performance of different downstream tasks. In real-world scenarios, performance can degrade sub…
cs.LG2024
Targeted Unlearning with Single Layer Unlearning Gradient
Zikui Cai, Yaoteng Tan, M. Salman Asif
Machine unlearning methods aim to remove sensitive or unwanted content from trained models, but typically demand extensive model updates at significant computational cost while pot…
cs.LG2023
Parameter-efficient Multi-Task and Multi-Domain Learning using Factorized Tensor Networks
Yash Garg, Nebiyou Yismaw, Rakib Hyder +2
Multi-task and multi-domain learning methods seek to learn multiple tasks/domains, jointly or one after another, using a single unified network. The primary challenge and opportuni…