no code implementations • 20 Dec 2024 • Erica Chiang, Divya Shanmugam, Ashley N. Beecy, Gabriel Sayer, Nir Uriel, Deborah Estrin, Nikhil Garg, Emma Pierson
Disease progression models are widely used to inform the diagnosis and treatment of many progressive diseases.
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 Million Song Dataset
(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).