1 citations · 1 across the 4 of their papers we have counts for
5 papers
Generalizable IoT Traffic Representations for Cross-Network Device Identification
Arunan Sivanathan, David Warren, Deepak Mishra +8
Machine learning models have demonstrated strong performance in classifying network traffic and identifying Internet-of-Things (IoT) devices, enabling operators to discover and man…
Negative to Positive Co-learning with Aggressive Modality Dropout
Nicholas Magal, Minh Tran, Riku Arakawa +1
This paper aims to document an effective way to improve multimodal co-learning by using aggressive modality dropout. We find that by using aggressive modality dropout we are able t…
Identity check problem for shallow quantum circuits
Sergey Bravyi, Natalie Parham, Minh Tran
Checking whether two quantum circuits are approximately equivalent is a common task in quantum computing. We consider a closely related identity check problem: given a quantum circ…
3FM: Multi-modal Meta-learning for Federated Tasks
Minh Tran, Roochi Shah, Zejun Gong
We present a novel approach in the domain of federated learning (FL), particularly focusing on addressing the challenges posed by modality heterogeneity, variability in modality av…
Scaling Cross-Domain Content-Based Image Retrieval for E-commerce Snap and Search Application
Isaac Kwan Yin Chung, Minh Tran, Eran Nussinovitch
In this industry talk at ECIR 2022, we illustrate how we approach the main challenges from large scale cross-domain content-based image retrieval using a cascade method and a combi…