14 citations · 24 across the 7 of their papers we have counts for
4 papers · 1 filter
Self-Supervised Learning with an Information Maximization Criterion
Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik +2
Self-supervised learning allows AI systems to learn effective representations from large amounts of data using tasks that do not require costly labeling. Mode collapse, i.e., the m…
An Information Maximization Based Blind Source Separation Approach for Dependent and Independent Sources
Alper T. Erdogan
We introduce a new information maximization (infomax) approach for the blind source separation problem. The proposed framework provides an information-theoretic perspective for det…
On Identifiable Polytope Characterization for Polytopic Matrix Factorization
Bariscan Bozkurt, Alper T. Erdogan
Polytopic matrix factorization (PMF) is a recently introduced matrix decomposition method in which the data vectors are modeled as linear transformations of samples from a polytope…
Polytopic Matrix Factorization: Determinant Maximization Based Criterion and Identifiability
Gokcan Tatli, Alper T. Erdogan
We introduce Polytopic Matrix Factorization (PMF) as a novel data decomposition approach. In this new framework, we model input data as unknown linear transformations of some laten…