16 citations · 26 across the 11 of their papers we have counts for
5 papers · 1 filter
ExpertNet: A Symbiosis of Classification and Clustering
Shivin Srivastava, Kenji Kawaguchi, Vaibhav Rajan
A widely used paradigm to improve the generalization performance of high-capacity neural models is through the addition of auxiliary unsupervised tasks during supervised training.…
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks
Hansheng Xue, Luwei Yang, Vaibhav Rajan +3
A bipartite network is a graph structure where nodes are from two distinct domains and only inter-domain interactions exist as edges. A large number of network embedding methods ex…
Clustering Aware Classification for Risk Prediction and Subtyping in Clinical Data
Shivin Srivastava, Siddharth Bhatia, Lingxiao Huang +3
In data containing heterogeneous subpopulations, classification performance benefits from incorporating the knowledge of cluster structure in the classifier. Previous methods for s…
Multi-way Spectral Clustering of Augmented Multi-view Data through Deep Collective Matrix Tri-factorization
Ragunathan Mariappan, Siva Rajesh Kasa, Vaibhav Rajan
We present the first deep learning based architecture for collective matrix tri-factorization (DCMTF) of arbitrary collections of matrices, also known as augmented multi-view data.…
Deep Collective Matrix Factorization for Augmented Multi-View Learning
Ragunathan Mariappan, Vaibhav Rajan
Learning by integrating multiple heterogeneous data sources is a common requirement in many tasks. Collective Matrix Factorization (CMF) is a technique to learn shared latent repre…