Personalized federated learning considers learning models unique to each...
Personalization methods in federated learning aim to balance the benefit...
Normalization methods such as batch normalization are commonly used in
o...
We consider the problem of estimating the parameters of a d-dimensional
...
We characterize the effectiveness of a natural and classic algorithm for...
Linear encoding of sparse vectors is widely popular, but is most commonl...
The facility location problem is widely used for summarizing large datas...
In this paper we present a new algorithm for computing a low rank
approx...