25 citations · 50 across the 10 of their papers we have counts for
4 papers · 1 filter
Subset Labeled LDA for Large-Scale Multi-Label Classification
Yannis Papanikolaou, Grigorios Tsoumakas
Labeled Latent Dirichlet Allocation (LLDA) is an extension of the standard unsupervised Latent Dirichlet Allocation (LDA) algorithm, to address multi-label learning tasks. Previous…
Large-Scale Online Semantic Indexing of Biomedical Articles via an Ensemble of Multi-Label Classification Models
Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis +2
Background: In this paper we present the approaches and methods employed in order to deal with a large scale multi-label semantic indexing task of biomedical papers. This work was…
Hierarchical Partitioning of the Output Space in Multi-label Data
Yannis Papanikolaou, Ioannis Katakis, Grigorios Tsoumakas
Hierarchy Of Multi-label classifiers (HOMER) is a multi-label learning algorithm that breaks the initial learning task to several, easier sub-tasks by first constructing a hierarch…
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA
Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin +1
We introduce a novel approach for estimating Latent Dirichlet Allocation (LDA) parameters from collapsed Gibbs samples (CGS), by leveraging the full conditional distributions over…