Machine learning algorithms

Federated Learning of Cohorts

Federated Learning of Cohorts (FLoC) is a type of web tracking. It groups people into "cohorts" based on their browsing history for the purpose of interest-based advertising. FLoC was being developed as a part of Google's Privacy Sandbox initiative, which includes several other advertising-related technologies with bird-themed names. Despite "federated learning" in the name, FLoC does not utilize any federated learning. Google began testing the technology in Chrome 89 released in March 2021 as a replacement for third-party cookies. By April 2021, every major browser aside from Google Chrome that is based on Google's open-source Chromium platform had declined to implement FLoC. The technology was criticized on privacy grounds by groups including the Electronic Frontier Foundation and DuckDuckGo, and has been described as anti-competitive; it generated an antitrust response in multiple countries as well as questions about General Data Protection Regulation compliance. In July 2021, Google quietly suspended development of FLoC; Chrome 93, released on August 31, 2021, became the first version which rendered FLoC feature void, but did not remove the internal programming. On January 25, 2022, Google officially announced it had ended development of FLoC technologies and proposed the new Topics API to replace it. (Wikipedia).

Federated Learning of Cohorts
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[deep learning] Federated Learning - training on decentralized data

Understanding Federated Learning. In order to secure the privacy of data, Federated Learning leaves the training data distributed on the mobile devices, and learns a shared model by aggregating locally-computed updates. all machine learning youtube videos from me, https://www.youtube.com/

From playlist Machine Learning

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Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients

A Google TechTalk, presented by Aritra Mitra, University of Pennsylvania, at the 2021 Google Federated Learning and Analytics Workshop, Nov. 8-10, 2021. For more information about the workshop: https://events.withgoogle.com/2021-workshop-on-federated-learning-and-analytics/#content

From playlist 2021 Google Workshop on Federated Learning and Analytics

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Academic Keynote: Federated Learning with Strange Gradients, Martin Jaggi (EPFL)

A Google TechTalk, presented by Martin Jaggi, 2021/11/8 ABSTRACT: Federated Learning with Strange Gradients. Collaborative learning methods such as federated learning are enabling many promising new applications for machine learning while respecting users' privacy. In this talk, we discus

From playlist 2021 Google Workshop on Federated Learning and Analytics

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Adaptive Federated Optimization

A Google TechTalk, 2020/7/30, presented by Zachary Charles, Google ABSTRACT:

From playlist 2020 Google Workshop on Federated Learning and Analytics

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Workshop on Federated Learning & Analytics: Pre-recorded Talks Day 1 Track 2 Q&A Privacy/Security

A Google TechTalk, 2020/7/29, presented by all Day Track 2 speakers ABSTRACT: Google Workshop on Federated Learning and Analytics: Pre-recorded Talks Day 1 Track 2 Question and Answer session on Privacy/Security

From playlist 2020 Google Workshop on Federated Learning and Analytics

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CaPC Learning: Confidential and Private Collaborative Learning

A Google TechTalk, presented by Adam Dziedzic, Vector Institute / University of Toronto, at the 2021 Google Federated Learning and Analytics Workshop, Nov. 8-10, 2021. For more information about the workshop: https://events.withgoogle.com/2021-workshop-on-federated-learning-and-analytics/

From playlist 2021 Google Workshop on Federated Learning and Analytics

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Federated learning with only positive labels and federated deep retrieval

A Google TechTalk, 2020/7/30, presented by Felix Yu, Google ABSTRACT:

From playlist 2020 Google Workshop on Federated Learning and Analytics

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Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization

A Google TechTalk, 2020/7/29, presented by Gauri Joshi, Carnegie Mellon University. ABSTRACT:

From playlist 2020 Google Workshop on Federated Learning and Analytics

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Day 1 Lightning Talks: Federated Optimization and Analytics

A Google TechTalk, presented by 8 Speakers, 2021/11/8 ABSTRACT: Lightning Talks are 7 minutes plus questions. Track 2 - Session Chair: Shanshan Wu (Federated Optimization & Analytics) 1. Peter Richtarik - EF21: A new, simpler, theoretically better, and practically faster error feedback

From playlist 2021 Google Workshop on Federated Learning and Analytics

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Kathy Hudson, National Institutes of Health - Stanford Medicine Big Data | Precision Health 2016

Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.

From playlist Big Data in Biomedicine: Enabling Precision Health Conference 2016

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Yale Digital Medicine Symposium 2019, Artificial Intelligence and Digital Medicine

Digital Medicine attracted over $8 Billion in venture capital in 2018 with promises of “driving down costs and empowering consumers to take charge of their health”. The Yale Digital Medicine Symposium explores the current state and future potential of digital health. Speakers included entr

From playlist Yale Digital Medicine Symposium 2019

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AIUK: AI in action (Session 1)

Hosted by Gemma Milne, this is the first of our AI in action demonstrations. These lively demos will feature the UK’s leading AI researchers showcasing their work across a range of topics. Join the audience to put your questions to the researchers live. --- The event took place via an

From playlist AIUK 2021

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Private Multi-Group Aggregation

A Google TechTalk, presented by Carolina Naim, Rutgers University, at the 2021 Google Federated Learning and Analytics Workshop, Nov. 8-10, 2021. For more information about the workshop: https://events.withgoogle.com/2021-workshop-on-federated-learning-and-analytics/#content

From playlist 2021 Google Workshop on Federated Learning and Analytics

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Christopher Longhurst, Stanford University - Stanford Big Data 2015

Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.

From playlist Big Data in Biomedicine Conference 2015

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Federated Learning and Analytics Research Using TensorFlow Federated

A Google TechTalk, presented by Google TFF Researchers, 2021/11/10 ABSTRACT: Sometimes centrally collecting data produced by edge devices, such as mobile phones, wearables, or cars, is infeasible or undesirable. With federated learning and analytics, clients collaboratively train a model o

From playlist 2021 Google Workshop on Federated Learning and Analytics

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Democracy Matters: Inequality and the American Dream

In this video, Ran Abramitzky, Debra Satz, Michael Boskin, David Grusky, and Florencia Torche discuss inequality and the American dream, particularly in relation to income and higher education. This video is part of a larger series entitled Democracy Matters, hosted by Ran Abramitzky on T

From playlist Democracy Matters

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Stanford Seminar - Federated Learning in Medicine: Breaking Down Silos to Advance Medical Research

Dr. Thomas Clozel OWKIN October 24, 2019 Thomas is the CEO and Co-Founder at OWKIN, leading medical research and business intelligence. He is a former Assistant Professor of Clinical Onco-Hematology at Hôpital Henri Mondor in Paris. Thomas is also a former member of Ari Melnick’s lab at t

From playlist EE402A - Topics in International Technology Management Seminar Series

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11. Low Fertility in Developed Countries (Guest Lecture by Michael Teitelbaum)

Global Problems of Population Growth (MCDB 150) Concerns about low fertility have been present in many countries for at least 100 years. A large population was considered essential to national power. But the issue is never simply a shortage of warm bodies: overall the world population h

From playlist Global Problems of Population Growth with Robert Wyman

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Machine Learning

If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.

From playlist Machine Learning

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Early Childhood Interventions. What Are They?

In the next year and a half, we here at Healthcare triage are going to take some deep dives into issues of health policy, especially those that touch on social determinants of health and health equity. The episodes that do so will be a bit longer than usual. They’ll look a little different

From playlist A Look at Early Childhood Programs

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SimHash | Device fingerprint | Federated learning