Recent years have witnessed the adoption of differential privacy (DP) in...
Algorithms for solving the linear classification problem have a long his...
The hybrid architecture of convolutional neural networks (CNNs) and
Tran...
Differential privacy (DP) allows data analysts to query databases that
c...
We study the problem of answering queries when (part of) the data may be...
Organizations often collect private data and release aggregate statistic...
Hyperparameter optimization is a ubiquitous challenge in machine learnin...
We present a method for producing unbiased parameter estimates and valid...
We study the variable selection problem in survival analysis to identify...
Organizations are increasingly relying on data to support decisions. Whe...
Correlation alignment (CORAL), a representative domain adaptation (DA)
a...
Differential privacy (DP) has arisen as the state-of-the-art metric for
...
Local sensitivity of a query Q given a database instance D, i.e. how muc...
Domain adaptation (DA) is used for adaptively obtaining labels of an
unp...
Local differential privacy (LDP) enables private data sharing and analyt...
Differential privacy has steadily become the de-facto standard for achie...
In this paper, we propose a Distributed Accumulated Newton Conjugate gra...
A private data federation is a set of autonomous databases that share a
...
Data cleaning is the process of detecting and repairing inaccurate or co...