Confidence-Constrained Maximum Entropy Framework for Learning from Multi-Instance Data

no code implementations • 7 Mar 2016 • Behrouz Behmardi, Forrest Briggs, Xiaoli Z. Fern, Raviv Raich

In this approach each bag is represented as a distribution using the principle of ME.

Novelty Detection Under Multi-Instance Multi-Label Framework

no code implementations • 25 Nov 2013 • Qi Lou, Raviv Raich, Forrest Briggs, Xiaoli Z. Fern

Contrary to the common assumption in MIML that each instance in a bag belongs to one of the known classes, in novelty detection, we focus on the scenario where bags may contain novel-class instances.

Novelty Detection Object +1

Multi-Label Classifier Chains for Bird Sound

no code implementations • 22 Apr 2013 • Forrest Briggs, Xiaoli Z. Fern, Jed Irvine

Bird sound data collected with unattended microphones for automatic surveys, or mobile devices for citizen science, typically contain multiple simultaneously vocalizing birds of different species.

General Classification Multi-Label Classification +1