Deep neural networks and decision trees operate on largely separate paradigms; typically,
the former performs representation learning with pre-specified architectures, while the latter …

Neural networks and tree ensembles are state-of-the-art learners, each with its unique
statistical and computational advantages. We aim to combine these advantages by …

Drowsy driving is one of the major causes of road accidents. The road accidents can be
avoided by the discrimination of alertness and drowsiness states of the drives. The …

How can we find the right graph for semi-supervised learning? In real world applications, the
choice of which edges to use for computation is the first step in any graph learning process …

Accumulated evidence has shown that commensal microorganisms play key roles in human
physiology and diseases. Dysbiosis of the human-associated microbial communities, often …

With the proliferation of machine learning applications in the real world, the demand for
explaining machine learning predictions continues to grow especially in high-stakes fields …

Decision Trees (DTs) like LambdaMART have been one of the most effective types of
learning-to-rank algorithms in the past decade. They typically work well with hand-crafted …

Floods are a natural calamity which leads the dry land to be submerged by water due to a
resurgence of a waterbody capacity which goes well beyond its natural limits leading to an …

In autonomous navigation, a planning system reasons about other agents to plan a safe and
plausible trajectory. Before planning starts, agents are typically processed with …

Estimating the suitability of individuals for a vocation via leveraging the knowledge within
cognitive factors comes with numerous applications: employment resourcing, occupation …