22 citations · 23 across the 5 of their papers we have counts for
3 papers · 1 filter
Unsupervised Deep Metric Learning via Orthogonality based Probabilistic Loss
Ujjal Kr Dutta, Mehrtash Harandi, Chellu Chandra Sekhar
Metric learning is an important problem in machine learning. It aims to group similar examples together. Existing state-of-the-art metric learning approaches require class labels t…
Affinity guided Geometric Semi-Supervised Metric Learning
Ujjal Kr Dutta, Mehrtash Harandi, Chellu Chandra Sekhar
In this paper, we revamp the forgotten classical Semi-Supervised Distance Metric Learning (SSDML) problem from a Riemannian geometric lens, to leverage stochastic optimization with…
A Probabilistic approach for Learning Embeddings without Supervision
Ujjal Kr Dutta, Mehrtash Harandi, Chandra Sekhar Chellu
For challenging machine learning problems such as zero-shot learning and fine-grained categorization, embedding learning is the machinery of choice because of its ability to learn…