Enterprises often own large collections of structured data in the form o...
The recent efforts in automation of machine learning or data science has...
Data Scientists leverage common sense reasoning and domain knowledge to
...
We address the relatively unexplored problem of hyper-parameter optimiza...
We address the relatively unexplored problem of hyper-parameter optimiza...
Data science and machine learning (DS/ML) are at the heart of the recent...
The CASH problem has been widely studied in the context of automated
con...
Data science is labor-intensive and human experts are scarce but heavily...
The rapid advancement of artificial intelligence (AI) is changing our li...
We study the automated machine learning (AutoML) problem of jointly sele...
Building a good predictive model requires an array of activities such as...
Application of neural networks to a vast variety of practical applicatio...
Electroencephalography (EEG) is an extensively-used and well-studied
tec...
Feature engineering is a crucial step in the process of predictive model...
A major challenge in designing neural network (NN) systems is to determi...
We study a novel machine learning (ML) problem setting of sequentially
a...
The ability to model search in a constraint solver can be an essential a...