Piyush Rai

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Indian Institute Of Technology, Madras ∙ Indian Institute of Technology Kanpur

Assistant Professor at Indian Institute of Technology, Kanpur; Adjunct Assistant Professor at Duke University

Towards Zero-Shot Learning with Fewer Seen Class Examples

We present a meta-learning based generative model for zero-shot learning...
11/14/2020 ∙ by Vinay Kumar Verma, et al. ∙ 1 ∙ share

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Generalized Adversarially Learned Inference

Allowing effective inference of latent vectors while training GANs can g...
06/15/2020 ∙ by Yatin Dandi, et al. ∙ 0 ∙ share

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Quantile Regularization: Towards Implicit Calibration of Regression Models

Recent works have shown that most deep learning models are often poorly ...
02/28/2020 ∙ by Saiteja Utpala, et al. ∙ 0 ∙ share

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A "Network Pruning Network" Approach to Deep Model Compression

We present a filter pruning approach for deep model compression, using a...
01/15/2020 ∙ by Vinay Kumar Verma, et al. ∙ 0 ∙ share

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Deep Attentive Ranking Networks for Learning to Order Sentences

We present an attention-based ranking framework for learning to order se...
12/31/2019 ∙ by Pawan Kumar, et al. ∙ 8 ∙ share

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Jointly Trained Image and Video Generation using Residual Vectors

In this work, we propose a modeling technique for jointly training image...
12/17/2019 ∙ by Yatin Dandi, et al. ∙ 17 ∙ share

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On the relationship between multitask neural networks and multitask Gaussian Processes

Despite the effectiveness of multitask deep neural network (MTDNN), ther...
12/12/2019 ∙ by Karthikeyan K, et al. ∙ 0 ∙ share

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Nonparametric Bayesian Structure Adaptation for Continual Learning

Continual Learning is a learning paradigm where machine learning models ...
12/08/2019 ∙ by Abhishek Kumar, et al. ∙ 0 ∙ share

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Refined α-Divergence Variational Inference via Rejection Sampling

We present an approximate inference method, based on a synergistic combi...
09/17/2019 ∙ by Rahul Sharma, et al. ∙ 0 ∙ share

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A Meta-Learning Framework for Generalized Zero-Shot Learning

Learning to classify unseen class samples at test time is popularly refe...
09/10/2019 ∙ by Vinay Kumar Verma, et al. ∙ 30 ∙ share

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A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation

In this paper, we present a domain adaptation based generative framework...
06/07/2019 ∙ by Varun Khare, et al. ∙ 0 ∙ share

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Stochastic Blockmodels meet Graph Neural Networks

Stochastic blockmodels (SBM) and their variants, e.g., mixed-membership ...
05/14/2019 ∙ by Nikhil Mehta, et al. ∙ 0 ∙ share

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Play and Prune: Adaptive Filter Pruning for Deep Model Compression

While convolutional neural networks (CNN) have achieved impressive perfo...
05/11/2019 ∙ by Pravendra Singh, et al. ∙ 0 ∙ share

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Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data

Many applications, such as text modelling, high-throughput sequencing, a...
05/02/2019 ∙ by He Zhao, et al. ∙ 0 ∙ share

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Generative Model for Zero-Shot Sketch-Based Image Retrieval

We present a probabilistic model for Sketch-Based Image Retrieval (SBIR)...
04/18/2019 ∙ by Vinay Kumar Verma, et al. ∙ 0 ∙ share

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HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs

We present a novel deep learning architecture in which the convolution o...
03/11/2019 ∙ by Pravendra Singh, et al. ∙ 0 ∙ share

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Leveraging Filter Correlations for Deep Model Compression

We present a filter correlation based model compression approach for dee...
11/26/2018 ∙ by Pravendra Singh, et al. ∙ 0 ∙ share

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Graph Convolutional Networks based Word Embeddings

Recently, word embeddings have been widely adopted across several NLP ap...
09/12/2018 ∙ by Shikhar Vashishth, et al. ∙ 0 ∙ share

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Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels

The latent feature relational model (LFRM) is a generative model for gra...
07/10/2018 ∙ by Gundeep Arora, et al. ∙ 0 ∙ share

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A Generative Approach to Zero-Shot and Few-Shot Action Recognition

We present a generative framework for zero-shot action recognition where...
01/27/2018 ∙ by Ashish Mishra, et al. ∙ 0 ∙ share

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Generalized Zero-Shot Learning via Synthesized Examples

We present a generative framework for generalized zero-shot learning whe...
12/11/2017 ∙ by Gundeep Arora, et al. ∙ 0 ∙ share

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Zero-Shot Learning via Class-Conditioned Deep Generative Models

We present a deep generative model for learning to predict classes not s...
11/15/2017 ∙ by Wenlin Wang, et al. ∙ 0 ∙ share

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Leveraging Distributional Semantics for Multi-Label Learning

We present a novel and scalable label embedding framework for large-scal...
09/18/2017 ∙ by Rahul Wadbude, et al. ∙ 0 ∙ share

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A Deep Generative Framework for Paraphrase Generation

Paraphrase generation is an important problem in NLP, especially in ques...
09/15/2017 ∙ by Ankush Gupta, et al. ∙ 0 ∙ share

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A Simple Exponential Family Framework for Zero-Shot Learning

We present a simple generative framework for learning to predict previou...
07/25/2017 ∙ by Vinay Kumar Verma, et al. ∙ 0 ∙ share

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Deep Generative Models for Relational Data with Side Information

We present a probabilistic framework for overlapping community discovery...
06/16/2017 ∙ by Changwei Hu, et al. ∙ 0 ∙ share

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Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data

We present a Bayesian non-negative tensor factorization model for count-...
08/18/2015 ∙ by Changwei Hu, et al. ∙ 0 ∙ share

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Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors

We present a scalable Bayesian model for low-rank factorization of massi...
08/18/2015 ∙ by Changwei Hu, et al. ∙ 0 ∙ share

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Flexible Modeling of Latent Task Structures in Multitask Learning

Multitask learning algorithms are typically designed assuming some fixed...
06/27/2012 ∙ by Alexandre Passos, et al. ∙ 0 ∙ share

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Piyush Rai

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