Piyush Rai

According to our database1, Piyush Rai authored at least 87 papers between 2008 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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On csauthors.net:

Bibliography

2022
Bayesian Federated Learning via Predictive Distribution Distillation.
CoRR, 2022

Spacing Loss for Discovering Novel Categories.
CoRR, 2022

Semi-Supervised Super-Resolution.
CoRR, 2022

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents.
CoRR, 2022

2021
SITA: Single Image Test-time Adaptation.
CoRR, 2021

NeurInt : Learning to Interpolate through Neural ODEs.
CoRR, 2021

Hypernetworks for Continual Semi-Supervised Learning.
CoRR, 2021

Variational Rejection Particle Filtering.
CoRR, 2021

Efficient Continual Adaptation for Generative Adversarial Networks.
CoRR, 2021

Towards Zero-Shot Learning with Fewer Seen Class Examples.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks.
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.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Bayesian Structural Adaptation for Continual Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Feature Transformations for Discriminative and Generative Continual Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Rectification-Based Knowledge Retention for Continual Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Fine-Grained Emotion Prediction by Modeling Emotion Definitions.
Proceedings of the 9th International Conference on Affective Computing and Intelligent Interaction, 2021

Few-Shot Lifelong Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Generalized Adversarially Learned Inference.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning.
IEEE J. Sel. Top. Signal Process., 2020

HetConv: Beyond Homogeneous Convolution Kernels for Deep CNNs.
Int. J. Comput. Vis., 2020

Quantile Regularization: Towards Implicit Calibration of Regression Models.
CoRR, 2020

A "Network Pruning Network" Approach to Deep Model Compression.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Leveraging Filter Correlations for Deep Model Compression.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Jointly Trained Image and Video Generation using Residual Vectors.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Calibrating CNNs for Lifelong Learning.
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.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Meta-Learning for Generalized Zero-Shot Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Graph Representation Learning via Ladder Gamma Variational Autoencoders.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Deep Attentive Ranking Networks for Learning to Order Sentences.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

P-SIF: Document Embeddings Using Partition Averaging.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
A flexible probabilistic framework for large-margin mixture of experts.
Mach. Learn., 2019

On the relationship between multitask neural networks and multitask Gaussian Processes.
CoRR, 2019

Nonparametric Bayesian Structure Adaptation for Continual Learning.
CoRR, 2019

Refined α-Divergence Variational Inference via Rejection Sampling.
CoRR, 2019

A Meta-Learning Framework for Generalized Zero-Shot Learning.
CoRR, 2019

Variational Autoencoders for Sparse and Overdispersed Discrete Data.
CoRR, 2019

Play and Prune: Adaptive Filter Pruning for Deep Model Compression.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Stochastic Blockmodels meet Graph Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Generative Model for Zero-Shot Sketch-Based Image Retrieval.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Deep Topic Models for Multi-label Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Distributional Semantics Meets Multi-Label Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Graph Convolutional Networks based Word Embeddings.
CoRR, 2018

A Generative Approach to Zero-Shot and Few-Shot Action Recognition.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Generalized Zero-Shot Learning via Synthesized Examples.
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.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Zero-Shot Learning via Class-Conditioned Deep Generative Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

A Deep Generative Framework for Paraphrase Generation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Leveraging Distributional Semantics for Multi-Label Learning.
CoRR, 2017

A Probabilistic Framework for Multi-Label Learning with Unseen Labels.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

A Simple Exponential Family Framework for Zero-Shot Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Scalable Generative Models for Multi-label Learning with Missing Labels.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Generative Models for Relational Data with Side Information.
Proceedings of the 34th International Conference on Machine Learning, 2017

Non-Negative Inductive Matrix Completion for Discrete Dyadic Data.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Earliness-Aware Deep Convolutional Networks for Early Time Series Classification.
CoRR, 2016

Deep Metric Learning with Data Summarization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Architecture-Adaptive Code Variant Tuning.
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.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings.
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.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Leveraging Features and Networks for Probabilistic Tensor Decomposition.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Learning Latent Structures Via Bayesian Nonparametrics: New Models and Efficient Interference.
PhD thesis, 2013

Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing.
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.
ACM Trans. Intell. Syst. Technol., 2012

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression.
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.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Online Learning of Multiple Tasks and Their Relationships.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Active Supervised Domain Adaptation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Co-regularized Multi-view Spectral Clustering.
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.
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.
Proceedings of the INFOCOM 2011. 30th IEEE International Conference on Computer Communications, 2011

Video Scene Segmentation with a Semantic Similarity.
Proceedings of the 5th Indian International Conference on Artificial Intelligence, 2011

Beam Search based MAP Estimates for the Indian Buffet Process.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Infinite Predictor Subspace Models for Multitask Learning.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Exploiting tag and word correlations for improved webpage clustering.
Proceedings of the 2nd International Workshop on Search and Mining User-Generated Contents, 2010

2009
Multi-Label Prediction via Sparse Infinite CCA.
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.
Proceedings of the IJCAI 2009, 2009

2008
The Infinite Hierarchical Factor Regression Model.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008


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