Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Efficient Framework for Clustered Federated Learning   We address the problem of federated learning (FL) where users are distributed
and partitioned into clusters. This setup captures settings where different
groups of users have their own objectives (learning tasks) but by aggregating
their data with others in the same cluster (same learning task), they can
leverage the strength in numbers in order to perform more efficient federated
learning. For this new framework of clustered federated learning, we propose
the Iterative Federated Clustering Algorithm (IFCA), which alternately
estimates the cluster identities of the users and optimizes model parameters
for the user clusters via gradient descent. We analyze the convergence rate of
this algorithm first in a linear model with squared loss and then for generic
strongly convex and smooth loss functions. We show that in both settings, with
good initialization, IFCA is guaranteed to converge, and discuss the optimality
of the statistical error rate. In particular, for the linear model with two
clusters, we can guarantee that our algorithm converges as long as the
initialization is slightly better than random. When the clustering structure is
ambiguous, we propose to train the models by combining IFCA with the weight
sharing technique in multi-task learning. In the experiments, we show that our
algorithm can succeed even if we relax the requirements on initialization with
random initialization and multiple restarts. We also present experimental
results showing that our algorithm is efficient in non-convex problems such as
neural networks. We demonstrate the benefits of IFCA over the baselines on
several clustered FL benchmarks.

26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
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The categories of this paper are: eess
17
The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys