Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FedML: A Research Library and Benchmark for Federated Machine Learning   Federated learning (FL) is a rapidly growing research field in machine
learning. However, existing FL libraries cannot adequately support diverse
algorithmic development; inconsistent dataset and model usage make fair
algorithm comparison challenging. In this work, we introduce FedML, an open
research library and benchmark to facilitate FL algorithm development and fair
performance comparison. FedML supports three computing paradigms: on-device
training for edge devices, distributed computing, and single-machine
simulation. FedML also promotes diverse algorithmic research with flexible and
generic API design and comprehensive reference baseline implementations
(optimizer, models, and datasets). We hope FedML could provide an efficient and
reproducible means for developing and evaluating FL algorithms that would
benefit the FL research community. We maintain the source code, documents, and
user community at https://fedml.ai.

24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex