1 code implementation • 3 Nov 2021 • Eugene Bagdasaryan, Peter Kairouz, Stefan Mellem, Adrià Gascón, Kallista Bonawitz, Deborah Estrin, Marco Gruteser
We design a scalable algorithm to privately generate location heatmaps over decentralized data from millions of user devices.
2 code implementations • 14 Mar 2020 • Kleomenis Katevas, Eugene Bagdasaryan, Jason Waterman, Mohamad Mounir Safadieh, Eleanor Birrell, Hamed Haddadi, Deborah Estrin
In this paper we present PoliFL, a decentralized, edge-based framework that supports heterogeneous privacy policies for federated learning.
no code implementations • 18 Apr 2019 • Longqi Yang, Chen Fang, Hailin Jin, Walter Chang, Deborah Estrin
Complex design tasks often require performing diverse actions in a specific order.
no code implementations • 25 Mar 2019 • David Hachuel, Akshay Jha, Deborah Estrin, Alfonso Martinez, Kyle Staller, Christopher Velez
Purpose - Functional bowel diseases, including irritable bowel syndrome, chronic constipation, and chronic diarrhea, are some of the most common diseases seen in clinical practice.
3 code implementations • 2 Jul 2018 • Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, Vitaly Shmatikov
An attacker selected in a single round of federated learning can cause the global model to immediately reach 100% accuracy on the backdoor task.
2 code implementations • WWW 2017 • Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge Belongie, Deborah Estrin
Metric learning algorithms produce distance metrics that capture the important relationships among data.
Ranked #1 on
Recommendation Systems
on MovieLens 20M
(Recall@100 metric)
2 code implementations • 25 May 2016 • Longqi Yang, Cheng-Kang Hsieh, Hongjian Yang, Nicola Dell, Serge Belongie, Curtis Cole, Deborah Estrin
We propose Yum-me, a personalized nutrient-based meal recommender system designed to meet individuals' nutritional expectations, dietary restrictions, and fine-grained food preferences.
no code implementations • 21 Dec 2015 • Longqi Yang, Cheng-Kang Hsieh, Deborah Estrin
User preference profiling is an important task in modern online social networks (OSN).