It is estimated that approximately 15
viral infections. The viruses that...
Automotive radar has increasingly attracted attention due to growing int...
Heterogeneity of data distributed across clients limits the performance ...
Federated learning (FL) is a privacy-promoting framework that enables
po...
Federated learning systems facilitate training of global models in setti...
Robust and accurate sensing is of critical importance for advancing
auto...
Federated learning (FL) enables distribution of machine learning workloa...
Pervasive computing applications commonly involve user's personal smartp...
In decentralized optimization, it is common algorithmic practice to have...
Identification of the type of communication technology and/or modulation...
Federated learning is a private and efficient framework for learning mod...
Machine learning methods allow us to make recommendations to users in
ap...
We are often interested in clustering objects that evolve over time and
...
Relational properties, e.g., the connectivity structure of nodes in a
di...
Background: Haplotypes, the ordered lists of single nucleotide variation...
Reconstructing components of a genomic mixture from data obtained by mea...
A variety of queries about stochastic systems boil down to study of Mark...
Many problems in discrete optimization can be formulated as the task of
...
The problem of organizing data that evolves over time into clusters is
e...
Single individual haplotyping is an NP-hard problem that emerges when
at...
We study the problem of sampling a bandlimited graph signal in the prese...
State-of-the-art algorithms for sparse subspace clustering perform spect...
We consider the Orthogonal Least-Squares (OLS) algorithm for the recover...
The Orthogonal Least Squares (OLS) algorithm sequentially selects column...
Sparse linear regression, which entails finding a sparse solution to an
...
Many in-hospital mortality risk prediction scores dichotomize predictive...