The rapid growth of remote sensing big data (RSBD) has attracted considerable attention
from both academia and industry. Despite the progress of computer technologies …

Visual neuroscience has traditionally focused much of its attention on understanding the
response properties of single neurons or neuronal ensembles. The visual white matter and …

Entity matching (EM) identifies data instances that refer to the same real-world entity, such
as (David Smith, UWMadison) and (DM Smith, UWM). This problem has been a long …

Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression
of tens of thousands of single cells simultaneously. We present DeepImpute, a deep neural …

In this paper, we present an overview of the Myria stack for big data management and
analytics that we developed in the database group at the University of Washington and that …

The quality of machine learning (ML) and deep learning (DL) models are very sensitive to
many different adjustable parameters that are set before training even begins, commonly …

Recent advances in cloud-based remote sensing platforms have revoluted the routines for
remote sensing big data (RSBD) analysis. However, it is challenging to make user-defined …

Differential privacy (DP) has become the gold standard in privacy-preserving data analytics,
but implementing it in realworld datasets and systems remains challenging. Recently …

Limited energy resources of sensor nodes in Wireless Sensor Networks (WSNs) make
energy consumption the most significant problem in practice. This paper proposes a novel …

Earth observation (EO) datasets are commonly provided as collection of scenes, where
individual scenes represent a temporal snapshot and cover a particular region on the Earth's …