ASAP DML: Deep Metric Learning with Alternating Sets of Alternating Proxies

no code implementations • 29 Sep 2021 • Yeti Z. Gürbüz, Oğul Can, A. Aydin Alatan

Deep metric learning (DML) aims to minimize empirical expected loss of the pairwise intra-/inter- class proximity violations in the embedding image.

Image Retrieval Metric Learning +1

Blind Deinterleaving of Signals in Time Series with Self-attention Based Soft Min-cost Flow Learning

no code implementations • 24 Oct 2020 • Oğul Can, Yeti Z. Gürbüz, Berkin Yıldırım, A. Aydin Alatan

We propose an end-to-end learning approach to address deinterleaving of patterns in time series, in particular, radar signals.

Clustering Time Series +1

Deep Metric Learning with Alternating Projections onto Feasible Sets

no code implementations • 17 Jul 2019 • Oğul Can, Yeti Ziya Gürbüz, A. Aydin Alatan

The feasible set induced by the constraint set is expressed as the intersection of the relaxed feasible sets which enforce the proximity constraints only for particular samples (a sample from each class) of the training data.

Clustering Image Retrieval +2