838 citations
- Microsoft Research (India)IN10 papers
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- Indian Institute of Technology KharagpurIN4 papers
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- Carnegie Mellon UniversityUS3 papers
- Indian Institute of Technology DelhiIN3 papers
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- Laboratoire Bordelais de Recherche en InformatiqueFR2 papers
9 papers · 1 filter
MMD-Regularized Unbalanced Optimal Transport
Piyushi Manupriya, J. Saketha Nath, Pratik Jawanpuria
We study the unbalanced optimal transport (UOT) problem, where the marginal constraints are enforced using Maximum Mean Discrepancy (MMD) regularization. Our work is motivated by t…
Statistical Optimal Transport posed as Learning Kernel Embedding
J. Saketha Nath, Pratik Jawanpuria
The objective in statistical Optimal Transport (OT) is to consistently estimate the optimal transport plan/map solely using samples from the given source and target marginal distri…
Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition
Anil R. Yelundur, Vineet Chaoji, Bamdev Mishra
Product reviews and ratings on e-commerce websites provide customers with detailed insights about various aspects of the product such as quality, usefulness, etc. Since they influe…
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
Pratik Jawanpuria, Arjun Balgovind, Anoop Kunchukuttan +1
We propose a novel geometric approach for learning bilingual mappings given monolingual embeddings and a bilingual dictionary. Our approach decouples learning the transformation fr…
FlashProfile: A Framework for Synthesizing Data Profiles
Saswat Padhi, Prateek Jain, Daniel Perelman +3
We address the problem of learning a syntactic profile for a collection of strings, i.e. a set of regex-like patterns that succinctly describe the syntactic variations in the strin…
A Riemannian gossip approach to subspace learning on Grassmann manifold
Bamdev Mishra, Hiroyuki Kasai, Pratik Jawanpuria +1
In this paper, we focus on subspace learning problems on the Grassmann manifold. Interesting applications in this setting include low-rank matrix completion and low-dimensional mul…