134 citations · 459 across the 38 of their papers we have counts for
6 papers · 1 filter
Generalized Zero-Shot Learning via Synthesized Examples
Vinay Kumar Verma, Gundeep Arora, Ashish Mishra +1
We present a generative framework for generalized zero-shot learning where the training and test classes are not necessarily disjoint. Built upon a variational autoencoder based ar…
Zero-Shot Learning via Class-Conditioned Deep Generative Models
Wenlin Wang, Yunchen Pu, Vinay Kumar Verma +5
We present a deep generative model for learning to predict classes not seen at training time. Unlike most existing methods for this problem, that represent each class as a point (v…
A Deep Generative Framework for Paraphrase Generation
Ankush Gupta, Arvind Agarwal, Prawaan Singh +1
Paraphrase generation is an important problem in NLP, especially in question answering, information retrieval, information extraction, conversation systems, to name a few. In this…
Leveraging Distributional Semantics for Multi-Label Learning
Rahul Wadbude, Vivek Gupta, Piyush Rai +3
We present a novel and scalable label embedding framework for large-scale multi-label learning a.k.a ExMLDS (Extreme Multi-Label Learning using Distributional Semantics). Our appro…
A Simple Exponential Family Framework for Zero-Shot Learning
Vinay Kumar Verma, Piyush Rai
We present a simple generative framework for learning to predict previously unseen classes, based on estimating class-attribute-gated class-conditional distributions. We model each…
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…