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Publication

SCAFFOLD Stochastic Controlled Averaging for Federated Learning

Sebastian Urban Stich, Sai Praneeth Reddy Karimireddy
2020
Conference Papers

Abstract

Federated Averaging (FEDAVG) has emerged as the algorithm of choice for federated learning due to its simplicity and low communication cost. However, in spite of recent research efforts, its performance is not fully understood. We obtain tight convergence rates for FEDAVG and prove that it suffers from 'client-drift' when the data is heterogeneous (non-iid), resulting in unstable and slow convergence.

Official source

https://infoscience.epfl.ch/entities/publication/f58f5ef3-2e36-4a6a-9f9b-fa56a65e90a4

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Sebastian Urban Stich, Sai Praneeth Reddy Karimireddy
2020
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/f58f5ef3-2e36-4a6a-9f9b-fa56a65e90a4

About this result

Related concepts (18)

Rate of convergence

In numerical analysis, the order of convergence and the rate of convergence of a convergent sequence are quantities that represent how quickly the sequence approaches its limit. A sequence that converges to is said to have order of convergence and rate of convergence if The rate of convergence is also called the asymptotic error constant. Note that this terminology is not standardized and some authors will use rate where this article uses order (e.g., ).

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

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