69 citations · 208 across the 40 of their papers we have counts for
41 papers
Implicit Bayes Adaptation: A Collaborative Transport Approach
Bo Jiang, Hamid Krim, Tianfu Wu +1
The power and flexibility of Optimal Transport (OT) have pervaded a wide spectrum of problems, including recent Machine Learning challenges such as unsupervised domain adaptation.…
Fast OT for Latent Domain Adaptation
Siddharth Roheda, Ashkan Panahi, Hamid Krim
In this paper, we address the problem of unsupervised Domain Adaptation. The need for such an adaptation arises when the distribution of the target data differs from that which is…
Information Fusion: Scaling Subspace-Driven Approaches
Sally Ghanem, Hamid Krim
In this work, we seek to exploit the deep structure of multi-modal data to robustly exploit the group subspace distribution of the information using the Convolutional Neural Networ…
Refining Self-Supervised Learning in Imaging: Beyond Linear Metric
Bo Jiang, Hamid Krim, Tianfu Wu +1
We introduce in this paper a new statistical perspective, exploiting the Jaccard similarity metric, as a measure-based metric to effectively invoke non-linear features in the loss…
Deep Transform and Metric Learning Networks
Wen Tang, Emilie Chouzenoux, Jean-Christophe Pesquet +1
Based on its great successes in inference and denosing tasks, Dictionary Learning (DL) and its related sparse optimization formulations have garnered a lot of research interest. Wh…
Latent Code-Based Fusion: A Volterra Neural Network Approach
Sally Ghanem, Siddharth Roheda, Hamid Krim
We propose a deep structure encoder using the recently introduced Volterra Neural Networks (VNNs) to seek a latent representation of multi-modal data whose features are jointly cap…