no code implementations • 13 Feb 2024 • Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy, Basak Guler, Ananthram Swami, Samet Oymak, Amit K. Roy-Chowdhury
The key premise of federated learning (FL) is to train ML models across a diverse set of data-owners (clients), without exchanging local data.
no code implementations • 6 Jan 2024 • Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy, Basak Guler, Ananthram Swami, Samet Oymak, Amit K. Roy-Chowdhury
Parameter-efficient tuning (PET) methods such as LoRA, Adapter, and Visual Prompt Tuning (VPT) have found success in enabling adaptation to new domains by tuning small modules within a transformer model.
no code implementations • 4 Jan 2024 • Sk Miraj Ahmed, Fahim Faisal Niloy, Dripta S. Raychaudhuri, Samet Oymak, Amit K. Roy-Chowdhury
Test time adaptation is the process of adapting, in an unsupervised manner, a pre-trained source model to each incoming batch of the test data (i. e., without requiring a substantial portion of the test data to be available, as in traditional domain adaptation) and without access to the source data.
no code implementations • 8 Nov 2023 • Fahim Faisal Niloy, Sk Miraj Ahmed, Dripta S. Raychaudhuri, Samet Oymak, Amit K. Roy-Chowdhury
By restoring the knowledge from the source, it effectively corrects the negative consequences arising from the gradual deterioration of model parameters caused by ongoing shifts in the domain.
1 code implementation • ICCV 2023 • Cody Simons, Dripta S. Raychaudhuri, Sk Miraj Ahmed, Suya You, Konstantinos Karydis, Amit K. Roy-Chowdhury
In this work, we relax both of these assumptions by addressing the problem of adapting a set of models trained independently on uni-modal data to a target domain consisting of unlabeled multi-modal data, without having access to the original source dataset.
no code implementations • 8 Sep 2022 • Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Amit K. Roy-Chowdhury
In such cases, transferring knowledge from a neural network trained on a well-labeled large dataset in the source modality (RGB) to a neural network that works on a target modality (depth, infrared, etc.)
1 code implementation • CVPR 2021 • Sk Miraj Ahmed, Dripta S. Raychaudhuri, Sujoy Paul, Samet Oymak, Amit K. Roy-Chowdhury
A recent line of work addressed this problem and proposed an algorithm that transfers knowledge to the unlabeled target domain from a single source model without requiring access to the source data.