We design a scalable algorithm to privately generate location heatmaps over decentralized data from millions of user devices.
In this paper we present PoliFL, a decentralized, edge-based framework that supports heterogeneous privacy policies for federated learning.
Complex design tasks often require performing diverse actions in a specific order.
Purpose - Functional bowel diseases, including irritable bowel syndrome, chronic constipation, and chronic diarrhea, are some of the most common diseases seen in clinical practice.
An attacker selected in a single round of federated learning can cause the global model to immediately reach 100% accuracy on the backdoor task.
Metric learning algorithms produce distance metrics that capture the important relationships among data.
Ranked #1 on Recommendation Systems on MovieLens 20M (Recall@100 metric)
We propose Yum-me, a personalized nutrient-based meal recommender system designed to meet individuals' nutritional expectations, dietary restrictions, and fine-grained food preferences.
User preference profiling is an important task in modern online social networks (OSN).