Feature selection is a crucial preprocessing step in data analytics and machine learning.
Classical feature selection algorithms select features based on the correlations between …

Neural architecture search (NAS) has attracted increasing attention. In recent years,
individual search methods have been replaced by weight-sharing search methods for higher …

Modern day computing increasingly relies on specialization to satiate growing performance
and efficiency requirements. A core challenge in designing such specialized hardware …

Radiation outcomes prediction (ROP) plays an important role in personalized prescription
and adaptive radiotherapy. A clinical decision may not only depend on an accurate radiation …

As Deep Learning (DL) systems are widely deployed for mission-critical applications,
debugging such systems becomes essential. Most existing works identify and repair …

We present a constraint-based algorithm for learning causal structures from observational
time-series data, in the presence of latent confounders. We assume a discrete-time …

During clinical practice, radiologists often use attributes, eg, morphological and appearance
characteristics of a lesion, to aid disease diagnosis. Effectively modeling attributes as well as …

Cancer is a complex disease, the understanding and treatment of which are being aided
through increases in the volume of collected data and in the scale of deployed computing …

Machine Learning for Data Science Handbook Lior Rokach Oded Maimon Erez Shmueli Editors
Machine Learning for Data Science Handbook Data Mining and Knowledge Discovery …

This article introduces the somatic transform that operationalizes the relation between affect
and cognition at the psychological level of analysis by capitalizing on the relation between …