Abbrevation
ACML
City
Beijing
Country
China
Deadline Paper
Start Date
End Date
Abstract

TOPICS<br>Topics of interest include but are not limited to:<br>1&#046; Learning problems<br>&#8211; Active learning<br>&#8211; Bayesian machine learning<br>&#8211; Deep learning, latent variable models<br>&#8211; Dimensionality reduction<br>&#8211; Feature selection<br>&#8211; Graphical models<br>&#8211; Learning for big data<br>&#8211; Learning in graphs<br>&#8211; Multiple instance learning<br>&#8211; Multi&#8211;objective learning<br>&#8211; Multi&#8211;task learning<br>&#8211; Semi&#8211;supervised learning<br>&#8211; Sparse learning<br>&#8211; Structured output learning<br>&#8211; Supervised learning<br>&#8211; Online learning<br>&#8211; Transfer learning<br>&#8211; Unsupervised learning<br>2&#046; Analysis of learning systems<br>&#8211; Computational learning theory<br>&#8211; Experimental evaluation<br>&#8211; Knowledge refinement<br>&#8211; Reproducible research<br>&#8211; Statistical learning theory<br>3&#046; Applications<br>&#8211; Bioinformatics<br>&#8211; Biomedical information<br>&#8211; Collaborative filtering<br>&#8211; Healthcare<br>&#8211; Computer vision<br>&#8211; Human activity recognition<br>&#8211; Information retrieval<br>&#8211; Natural language processing<br>&#8211; Social networks<br>&#8211; Web search<br>4&#046; Learning in knowledge&#8211;intensive systems<br>&#8211; Knowledge refinement and theory revision<br>&#8211; Multi&#8211;strategy learning<br>&#8211; Other systems<br>