Piyush Rai

According to our database, Piyush Rai authored at least 96 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Rectification-Based Knowledge Retention for Task Incremental Learning.

Pratik Mazumder, Pravendra Singh, Piyush Rai, Vinay P. Namboodiri

IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Text-Based Fine-Grained Emotion Prediction.

Gargi Singh, Dhanajit Brahma, Piyush Rai, Ashutosh Modi

IEEE Trans. Affect. Comput., 2024

RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance.

Avideep Mukherjee, Soumya Banerjee, Vinay P. Namboodiri, Piyush Rai

CoRR, 2024

Robust Black-box Testing of Deep Neural Networks using Co-Domain Coverage.

Aishwarya Gupta, Indranil Saha, Piyush Rai

CoRR, 2024

VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference.

Soumya Banerjee, Vinay Kumar Verma, Avideep Mukherjee, Deepak Gupta, Vinay P. Namboodiri, Piyush Rai

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

A Probabilistic Framework for Lifelong Test-Time Adaptation.

Dhanajit Brahma, Piyush Rai

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Gradient Perturbation-based Efficient Deep Ensembles.

Amit Chandak, Purushottam Kar, Piyush Rai

Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD), 2023

Federated Learning with Uncertainty via Distilled Predictive Distributions.

Shrey Bhatt, Aishwarya Gupta, Piyush Rai

Proceedings of the Asian Conference on Machine Learning, 2023

2022

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents.

Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar

Trans. Mach. Learn. Res., 2022

Bayesian Federated Learning via Predictive Distribution Distillation.

Shrey Bhatt, Aishwarya Gupta, Piyush Rai

CoRR, 2022

Semi-Supervised Super-Resolution.

Ankur Singh, Piyush Rai

CoRR, 2022

Novel Class Discovery Without Forgetting.

K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian

Proceedings of the Computer Vision, 2022

Spacing Loss for Discovering Novel Categories.

K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

SITA: Single Image Test-time Adaptation.

Ansh Khurana, Sujoy Paul, Piyush Rai, Soma Biswas, Gaurav Aggarwal

CoRR, 2021

NeurInt : Learning to Interpolate through Neural ODEs.

Avinandan Bose, Aniket Das, Yatin Dandi, Piyush Rai

CoRR, 2021

Hypernetworks for Continual Semi-Supervised Learning.

Dhanajit Brahma, Vinay Kumar Verma, Piyush Rai

CoRR, 2021

Variational Rejection Particle Filtering.

Rahul Sharma, Soumya Banerjee, Dootika Vats, Piyush Rai

CoRR, 2021

Efficient Continual Adaptation for Generative Adversarial Networks.

Sakshi Varshney, Vinay Kumar Verma, Lawrence Carin, Piyush Rai

CoRR, 2021

Towards Zero-Shot Learning with Fewer Seen Class Examples.

Vinay Kumar Verma, Ashish Mishra, Anubha Pandey, Hema A. Murthy, Piyush Rai

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks.

Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Knowledge Consolidation based Class Incremental Online Learning with Limited Data.

Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Bayesian Structural Adaptation for Continual Learning.

Abhishek Kumar, Sunabha Chatterjee, Piyush Rai

Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Feature Transformations for Discriminative and Generative Continual Learning.

Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Rectification-Based Knowledge Retention for Continual Learning.

Pravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Fine-Grained Emotion Prediction by Modeling Emotion Definitions.

Gargi Singh, Dhanajit Brahma, Piyush Rai, Ashutosh Modi

Proceedings of the 9th International Conference on Affective Computing and Intelligent Interaction, 2021

Few-Shot Lifelong Learning.

Pratik Mazumder, Pravendra Singh, Piyush Rai

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Generalized Adversarially Learned Inference.

Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning.

Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

IEEE J. Sel. Top. Signal Process., 2020

HetConv: Beyond Homogeneous Convolution Kernels for Deep CNNs.

Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

Int. J. Comput. Vis., 2020

Quantile Regularization: Towards Implicit Calibration of Regression Models.

Saiteja Utpala, Piyush Rai

CoRR, 2020

A "Network Pruning Network" Approach to Deep Model Compression.

Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Leveraging Filter Correlations for Deep Model Compression.

Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

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

Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Jointly Trained Image and Video Generation using Residual Vectors.

Yatin Dandi, Aniket Das, Soumye Singhal, Vinay P. Namboodiri, Piyush Rai

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Calibrating CNNs for Lifelong Learning.

Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Variational Autoencoders for Sparse and Overdispersed Discrete Data.

He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Meta-Learning for Generalized Zero-Shot Learning.

Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Graph Representation Learning via Ladder Gamma Variational Autoencoders.

Arindam Sarkar, Nikhil Mehta, Piyush Rai

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Deep Attentive Ranking Networks for Learning to Order Sentences.

Pawan Kumar, Dhanajit Brahma, Harish Karnick, Piyush Rai

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

P-SIF: Document Embeddings Using Partition Averaging.

Vivek Gupta, Ankit Saw, Pegah Nokhiz, Praneeth Netrapalli, Piyush Rai, Partha P. Talukdar

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A flexible probabilistic framework for large-margin mixture of experts.

Archit Sharma, Siddhartha Saxena, Piyush Rai

Mach. Learn., 2019

On the relationship between multitask neural networks and multitask Gaussian Processes.

Karthikeyan K, Shubham Kumar Bharti, Piyush Rai

CoRR, 2019

Nonparametric Bayesian Structure Adaptation for Continual Learning.

Abhishek Kumar, Sunabha Chatterjee, Piyush Rai

CoRR, 2019

Refined α-Divergence Variational Inference via Rejection Sampling.

Rahul Sharma, Abhishek Kumar, Piyush Rai

CoRR, 2019

A Meta-Learning Framework for Generalized Zero-Shot Learning.

Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai

CoRR, 2019

Variational Autoencoders for Sparse and Overdispersed Discrete Data.

He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Mingyuan Zhou

CoRR, 2019

Play and Prune: Adaptive Filter Pruning for Deep Model Compression.

Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Stochastic Blockmodels meet Graph Neural Networks.

Nikhil Mehta, Lawrence Carin, Piyush Rai

Proceedings of the 36th International Conference on Machine Learning, 2019

Generative Model for Zero-Shot Sketch-Based Image Retrieval.

Vinay Kumar Verma, Aakansha Mishra, Ashish Mishra, Piyush Rai

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs.

Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Deep Topic Models for Multi-label Learning.

Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks.

Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Distributional Semantics Meets Multi-Label Learning.

Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain, Piyush Rai

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Graph Convolutional Networks based Word Embeddings.

Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar

CoRR, 2018

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

Ashish Mishra, Vinay Kumar Verma, M. Shiva Krishna Reddy, Arulkumar Subramaniam, Piyush Rai, Anurag Mittal

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels.

Gundeep Arora, Anupreet Porwal, Kanupriya Agarwal, Avani Samdariya, Piyush Rai

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Generalized Zero-Shot Learning via Synthesized Examples.

Vinay Kumar Verma, Gundeep Arora, Ashish Mishra, Piyush Rai

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences.

He Zhao, Piyush Rai, Lan Du, Wray L. Buntine

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Zero-Shot Learning via Class-Conditioned Deep Generative Models.

Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

A Deep Generative Framework for Paraphrase Generation.

Ankush Gupta, Arvind Agarwal, Prawaan Singh, Piyush Rai

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Leveraging Distributional Semantics for Multi-Label Learning.

Rahul Wadbude, Vivek Gupta, Piyush Rai, Nagarajan Natarajan, Harish Karnick

CoRR, 2017

A Probabilistic Framework for Multi-Label Learning with Unseen Labels.

Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

A Simple Exponential Family Framework for Zero-Shot Learning.

Vinay Kumar Verma, Piyush Rai

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Scalable Generative Models for Multi-label Learning with Missing Labels.

Vikas Jain, Nirbhay Modhe, Piyush Rai

Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Generative Models for Relational Data with Side Information.

Changwei Hu, Piyush Rai, Lawrence Carin

Proceedings of the 34th International Conference on Machine Learning, 2017

Non-Negative Inductive Matrix Completion for Discrete Dyadic Data.

Piyush Rai

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Earliness-Aware Deep Convolutional Networks for Early Time Series Classification.

Wenlin Wang, Changyou Chen, Wenqi Wang, Piyush Rai, Lawrence Carin

CoRR, 2016

Deep Metric Learning with Data Summarization.

Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Architecture-Adaptive Code Variant Tuning.

Saurav Muralidharan, Amit Roy, Mary W. Hall, Michael Garland, Piyush Rai

Proceedings of the Twenty-First International Conference on Architectural Support for Programming Languages and Operating Systems, 2016

Topic-Based Embeddings for Learning from Large Knowledge Graphs.

Changwei Hu, Piyush Rai, Lawrence Carin

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information.

Changwei Hu, Piyush Rai, Lawrence Carin

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors.

Changwei Hu, Piyush Rai, Lawrence Carin

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data.

Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings.

Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Scalable Probabilistic Tensor Factorization for Binary and Count Data.

Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision.

Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Leveraging Features and Networks for Probabilistic Tensor Decomposition.

Piyush Rai, Yingjian Wang, Lawrence Carin

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data.

Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors.

Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David B. Dunson, Lawrence Carin

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Learning Latent Structures Via Bayesian Nonparametrics: New Models and Efficient Interference.

Piyush Rai

PhD thesis, 2013

Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing.

Joyce Jiyoung Whang, Piyush Rai, Inderjit S. Dhillon

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Leveraging Social Bookmarks from Partially Tagged Corpus for Improved Web Page Clustering.

Anusua Trivedi, Piyush Rai, Hal Daumé III, Scott L. DuVall

ACM Trans. Intell. Syst. Technol., 2012

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression.

Piyush Rai, Abhishek Kumar, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Flexible Modeling of Latent Task Structures in Multitask Learning.

Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daumé III

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Online Learning of Multiple Tasks and Their Relationships.

Avishek Saha, Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Active Supervised Domain Adaptation.

Avishek Saha, Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian, Scott L. DuVall

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Co-regularized Multi-view Spectral Clustering.

Abhishek Kumar, Piyush Rai, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Message-Passing for Approximate MAP Inference with Latent Variables.

Jiarong Jiang, Piyush Rai, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Distinguishing locations across perimeters using wireless link measurements.

Junxing Zhang, Sneha Kumar Kasera, Neal Patwari, Piyush Rai

Proceedings of the INFOCOM 2011. 30th IEEE International Conference on Computer Communications, 2011

Video Scene Segmentation with a Semantic Similarity.

Niraj Kumar, Piyush Rai, Chandrika Pulla, C. V. Jawahar

Proceedings of the 5th Indian International Conference on Artificial Intelligence, 2011

Beam Search based MAP Estimates for the Indian Buffet Process.

Piyush Rai, Hal Daumé III

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Infinite Predictor Subspace Models for Multitask Learning.

Piyush Rai, Hal Daumé III

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Exploiting tag and word correlations for improved webpage clustering.

Anusua Trivedi, Piyush Rai, Scott L. DuVall, Hal Daumé III

Proceedings of the 2nd International Workshop on Search and Mining User-Generated Contents, 2010

2009

Multi-Label Prediction via Sparse Infinite CCA.

Piyush Rai, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Streamed Learning: One-Pass SVMs.

Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian

Proceedings of the IJCAI 2009, 2009

2008

The Infinite Hierarchical Factor Regression Model.

Piyush Rai, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 21, 2008