Visual domain adaptation addresses the problem of adapting the sample distribution of the source domain to the target domain, where the recognition task is intended but the data d...
We present a novel framework to estimate protein-protein (PPI) and domain-domain (DDI) interactions based on a belief propagation estimation method that efficiently computes inter...
Faruck Morcos, Marcin Sikora, Mark S. Alber, Dale ...
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in our understanding o...
This paper investigates the utilization of the master-slave (MS) paradigm as an alternative to domain decomposition (DD) methods for parallelizing lattice gauge theory (LGT) model...