Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Model-sharing Games: Analyzing Federated Learning Under Voluntary
  Participation   Federated learning is a setting where agents, each with access to their own
data source, combine models from local data to create a global model. If agents
are drawing their data from different distributions, though, federated learning
might produce a biased global model that is not optimal for each agent. This
means that agents face a fundamental question: should they choose the global
model or their local model? We show how this situation can be naturally
analyzed through the framework of coalitional game theory.
  We propose the following game: there are heterogeneous players with different
model parameters governing their data distribution and different amounts of
data they have noisily drawn from their own distribution. Each player's goal is
to obtain a model with minimal expected mean squared error (MSE) on their own
distribution. They have a choice of fitting a model based solely on their own
data, or combining their learned parameters with those of some subset of the
other players. Combining models reduces the variance component of their error
through access to more data, but increases the bias because of the
heterogeneity of distributions.
  Here, we derive exact expected MSE values for problems in linear regression
and mean estimation. We then analyze the resulting game in the framework of
hedonic game theory; we study how players might divide into coalitions, where
each set of players within a coalition jointly construct model(s). We analyze
three methods of federation, modeling differing degrees of customization. In
uniform federation, the agents collectively produce a single model. In
coarse-grained federation, each agent can weight the global model together with
their local model. In fine-grained federation, each agent can flexibly combine
models from all other agents in the federation. For each method, we analyze the
stable partitions of players into coalitions.

26
The categories of this paper are: bayes-an
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph