Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …

Zeroth-order (ZO) optimization is a subset of gradient-free optimization that emerges in many
signal processing and machine learning (ML) applications. It is used for solving optimization …

Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …

Automated Machine Learning (AutoML) supports practitioners and researchers with the
tedious task of designing machine learning pipelines and has recently achieved substantial …

Today, the prominence of data science within organizations has given rise to teams of data
science workers collaborating on extracting insights from data, as opposed to individual data …

The deployment constraints in practical applications necessitate the pruning of large-scale
deep learning models, ie, promoting their weight sparsity. As illustrated by the Lottery Ticket …

We explore trust in a relatively new area of data science: Automated Machine Learning
(AutoML). In AutoML, AI methods are used to generate and optimize machine learning …

Computational notebooks allow data scientists to express their ideas through a combination
of code and documentation. However, data scientists often pay attention only to the code …

Data science (DS) projects often follow a lifecycle that consists of laborious tasks for data
scientists and domain experts (eg, data exploration, model training, etc.). Only till recently …

Creating presentation slides is a critical but time-consuming task for data scientists. While
researchers have proposed many AI techniques to lift data scientists' burden on data …