134 citations · 459 across the 38 of their papers we have counts for
5 papers · 1 filter
A Meta-Learning Framework for Generalized Zero-Shot Learning
Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai
Learning to classify unseen class samples at test time is popularly referred to as zero-shot learning (ZSL). If test samples can be from training (seen) as well as unseen classes,…
Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels
Gundeep Arora, Anupreet Porwal, Kanupriya Agarwal +2
The latent feature relational model (LFRM) is a generative model for graph-structured data to learn a binary vector representation for each node in the graph. The binary vector den…
Deep Generative Models for Relational Data with Side Information
Changwei Hu, Piyush Rai, Lawrence Carin
We present a probabilistic framework for overlapping community discovery and link prediction for relational data, given as a graph. The proposed framework has: (1) a deep architect…
Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data
Changwei Hu, Piyush Rai, Changyou Chen +2
We present a Bayesian non-negative tensor factorization model for count-valued tensor data, and develop scalable inference algorithms (both batch and online) for dealing with massi…
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors
Changwei Hu, Piyush Rai, Lawrence Carin
We present a scalable Bayesian model for low-rank factorization of massive tensors with binary observations. The proposed model has the following key properties: (1) in contrast to…