Piyush Rai - RankMe

135 papers A* 36A 16B 1C 1Journal 63Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Probing Layer-wise Memorization and Generalization in Deep Neural Networks via Model Stitching. Trans. Mach. Learn. Res. Aishwarya Gupta, Indranil Saha, Piyush Rai
2025	J	`jnl`	Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization. Trans. Mach. Learn. Res. Shivam Pal, Aishwarya Gupta, Saqib Sarwar, Piyush Rai
2025	J	`jnl`	NOVO: Unlearning-Compliant Vision Transformers. CoRR Soumya Roy, Soumya Banerjee, Vinay Kumar Verma, Soumik Dasgupta, Deepak Gupta, Piyush Rai
2025	J	`jnl`	Shortcut Invariance: Targeted Jacobian Regularization in Disentangled Latent Space. CoRR Shivam Pal, Sakshi Varshney, Piyush Rai
2024	J	`jnl`	Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization. CoRR Shivam Pal, Aishwarya Gupta, Saqib Sarwar, Piyush Rai
2024	A	`conf`	RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance. BMVC Avideep Mukherjee, Soumya Banerjee, Piyush Rai, Vinay P. Namboodiri
2024	J	`jnl`	RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance. CoRR Avideep Mukherjee, Soumya Banerjee, Vinay P. Namboodiri, Piyush Rai
2024	J	`jnl`	Rectification-Based Knowledge Retention for Task Incremental Learning. IEEE Trans. Pattern Anal. Mach. Intell. Pratik Mazumder, Pravendra Singh, Piyush Rai, Vinay P. Namboodiri
2024	J	`jnl`	Robust Black-box Testing of Deep Neural Networks using Co-Domain Coverage. CoRR Aishwarya Gupta, Indranil Saha, Piyush Rai
2024	J	`jnl`	Spatio-Temporal Forecasting of PM2.5 via Spatial-Diffusion guided Encoder-Decoder Architecture. CoRR Malay Pandey, Vaishali Jain, Nimit Godhani, Sachchida Nand Tripathi, Piyush Rai
2024	J	`jnl`	Text-Based Fine-Grained Emotion Prediction. IEEE Trans. Affect. Comput. Gargi Singh, Dhanajit Brahma, Piyush Rai, Ashutosh Modi
2024	A*	`conf`	VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference. ICRA Soumya Banerjee, Vinay Kumar Verma, Avideep Mukherjee, Deepak Gupta, Vinay P. Namboodiri, Piyush Rai
2023	A*	`conf`	A Probabilistic Framework for Lifelong Test-Time Adaptation. CVPR Dhanajit Brahma, Piyush Rai
2023	C	`conf`	Federated Learning with Uncertainty via Distilled Predictive Distributions. ACML Shrey Bhatt, Aishwarya Gupta, Piyush Rai
2023	—	`conf`	Gradient Perturbation-based Efficient Deep Ensembles. COMAD/CODS Amit Chandak, Purushottam Kar, Piyush Rai
2023	J	`jnl`	VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference. CoRR Soumya Banerjee, Vinay Kumar Verma, Avideep Mukherjee, Deepak Gupta, Vinay P. Namboodiri, Piyush Rai
2022	J	`jnl`	A Probabilistic Framework for Lifelong Test-Time Adaptation. CoRR Dhanajit Brahma, Piyush Rai
2022	J	`jnl`	Bayesian Federated Learning via Predictive Distribution Distillation. CoRR Shrey Bhatt, Aishwarya Gupta, Piyush Rai
2022	J	`jnl`	DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents. CoRR Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
2022	J	`jnl`	DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents. Trans. Mach. Learn. Res. Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
2022	—	`conf`	Novel Class Discovery Without Forgetting. ECCV (24) K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian
2022	J	`jnl`	Novel Class Discovery without Forgetting. CoRR K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian
2022	J	`jnl`	Semi-Supervised Super-Resolution. CoRR Ankur Singh, Piyush Rai
2022	—	`conf`	Spacing Loss for Discovering Novel Categories. CVPR Workshops K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian
2022	J	`jnl`	Spacing Loss for Discovering Novel Categories. CoRR K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian
2021	A*	`conf`	Bayesian Structural Adaptation for Continual Learning. ICML Abhishek Kumar, Sunabha Chatterjee, Piyush Rai
2021	A*	`conf`	CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks. NeurIPS Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai
2021	J	`jnl`	Efficient Continual Adaptation for Generative Adversarial Networks. CoRR Sakshi Varshney, Vinay Kumar Verma, Lawrence Carin, Piyush Rai
2021	A*	`conf`	Efficient Feature Transformations for Discriminative and Generative Continual Learning. CVPR Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin
2021	J	`jnl`	Efficient Feature Transformations for Discriminative and Generative Continual Learning. CoRR Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin
2021	A*	`conf`	Few-Shot Lifelong Learning. AAAI Pratik Mazumder, Pravendra Singh, Piyush Rai
2021	J	`jnl`	Few-Shot Lifelong Learning. CoRR Pratik Mazumder, Pravendra Singh, Piyush Rai
2021	B	`conf`	Fine-Grained Emotion Prediction by Modeling Emotion Definitions. ACII Gargi Singh, Dhanajit Brahma, Piyush Rai, Ashutosh Modi
2021	J	`jnl`	Fine-Grained Emotion Prediction by Modeling Emotion Definitions. CoRR Gargi Singh, Dhanajit Brahma, Piyush Rai, Ashutosh Modi
2021	A*	`conf`	Generalized Adversarially Learned Inference. AAAI Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai
2021	J	`jnl`	Hypernetworks for Continual Semi-Supervised Learning. CoRR Dhanajit Brahma, Vinay Kumar Verma, Piyush Rai
2021	A*	`conf`	Knowledge Consolidation based Class Incremental Online Learning with Limited Data. IJCAI Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai
2021	J	`jnl`	Knowledge Consolidation based Class Incremental Online Learning with Limited Data. CoRR Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai
2021	J	`jnl`	NeurInt : Learning to Interpolate through Neural ODEs. CoRR Avinandan Bose, Aniket Das, Yatin Dandi, Piyush Rai
2021	A*	`conf`	Rectification-Based Knowledge Retention for Continual Learning. CVPR Pravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri
2021	J	`jnl`	Rectification-based Knowledge Retention for Continual Learning. CoRR Pravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri
2021	J	`jnl`	SITA: Single Image Test-time Adaptation. CoRR Ansh Khurana, Sujoy Paul, Piyush Rai, Soma Biswas, Gaurav Aggarwal
2021	A	`conf`	Towards Zero-Shot Learning with Fewer Seen Class Examples. WACV Vinay Kumar Verma, Ashish Mishra, Anubha Pandey, Hema A. Murthy, Piyush Rai
2021	J	`jnl`	Variational Rejection Particle Filtering. CoRR Rahul Sharma, Soumya Banerjee, Dootika Vats, Piyush Rai
2020	A	`conf`	A "Network Pruning Network" Approach to Deep Model Compression. WACV Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai
2020	J	`jnl`	A "Network Pruning Network" Approach to Deep Model Compression. CoRR Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai
2020	A	`conf`	A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation. WACV Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai
2020	J	`jnl`	Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning. IEEE J. Sel. Top. Signal Process. Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2020	A*	`conf`	Calibrating CNNs for Lifelong Learning. NeurIPS Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai
2020	A*	`conf`	Deep Attentive Ranking Networks for Learning to Order Sentences. AAAI Pawan Kumar, Dhanajit Brahma, Harish Karnick, Piyush Rai
2020	J	`jnl`	Deep Attentive Ranking Networks for Learning to Order Sentences. CoRR Pawan Kumar, Dhanajit Brahma, Harish Karnick, Piyush Rai
2020	J	`jnl`	Generalized Adversarially Learned Inference. CoRR Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai
2020	A*	`conf`	Graph Representation Learning via Ladder Gamma Variational Autoencoders. AAAI Arindam Sarkar, Nikhil Mehta, Piyush Rai
2020	J	`jnl`	HetConv: Beyond Homogeneous Convolution Kernels for Deep CNNs. Int. J. Comput. Vis. Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2020	A	`conf`	Jointly Trained Image and Video Generation using Residual Vectors. WACV Yatin Dandi, Aniket Das, Soumye Singhal, Vinay P. Namboodiri, Piyush Rai
2020	A	`conf`	Leveraging Filter Correlations for Deep Model Compression. WACV Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2020	A*	`conf`	Meta-Learning for Generalized Zero-Shot Learning. AAAI Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai
2020	A*	`conf`	P-SIF: Document Embeddings Using Partition Averaging. AAAI Vivek Gupta, Ankit Saw, Pegah Nokhiz, Praneeth Netrapalli, Piyush Rai, Partha P. Talukdar
2020	J	`jnl`	P-SIF: Document Embeddings Using Partition Averaging. CoRR Vivek Gupta, Ankit Saw, Pegah Nokhiz, Praneeth Netrapalli, Piyush Rai, Partha P. Talukdar
2020	J	`jnl`	Quantile Regularization: Towards Implicit Calibration of Regression Models. CoRR Saiteja Utpala, Piyush Rai
2020	J	`jnl`	Towards Zero-Shot Learning with Fewer Seen Class Examples. CoRR Vinay Kumar Verma, Ashish Mishra, Anubha Pandey, Hema A. Murthy, Piyush Rai
2020	A	`conf`	Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou
2019	J	`jnl`	A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation. CoRR Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai
2019	J	`jnl`	A Meta-Learning Framework for Generalized Zero-Shot Learning. CoRR Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai
2019	J	`jnl`	A flexible probabilistic framework for large-margin mixture of experts. Mach. Learn. Archit Sharma, Siddhartha Saxena, Piyush Rai
2019	A	`conf`	Deep Topic Models for Multi-label Learning. AISTATS Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai
2019	A*	`conf`	Distributional Semantics Meets Multi-Label Learning. AAAI Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain, Piyush Rai
2019	—	`conf`	Generative Model for Zero-Shot Sketch-Based Image Retrieval. CVPR Workshops Vinay Kumar Verma, Aakansha Mishra, Ashish Mishra, Piyush Rai
2019	J	`jnl`	Generative Model for Zero-Shot Sketch-Based Image Retrieval. CoRR Vinay Kumar Verma, Aakansha Mishra, Ashish Mishra, Piyush Rai
2019	A*	`conf`	HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs. CVPR Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2019	J	`jnl`	HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs. CoRR Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2019	—	`conf`	Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks. ACL (1) Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar
2019	J	`jnl`	Jointly Trained Image and Video Generation using Residual Vectors. CoRR Yatin Dandi, Aniket Das, Soumye Singhal, Vinay P. Namboodiri, Piyush Rai
2019	J	`jnl`	Nonparametric Bayesian Structure Adaptation for Continual Learning. CoRR Abhishek Kumar, Sunabha Chatterjee, Piyush Rai
2019	J	`jnl`	On the relationship between multitask neural networks and multitask Gaussian Processes. CoRR Karthikeyan K, Shubham Kumar Bharti, Piyush Rai
2019	A*	`conf`	Play and Prune: Adaptive Filter Pruning for Deep Model Compression. IJCAI Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2019	J	`jnl`	Play and Prune: Adaptive Filter Pruning for Deep Model Compression. CoRR Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2019	J	`jnl`	Refined α-Divergence Variational Inference via Rejection Sampling. CoRR Rahul Sharma, Abhishek Kumar, Piyush Rai
2019	A*	`conf`	Stochastic Blockmodels meet Graph Neural Networks. ICML Nikhil Mehta, Lawrence Carin, Piyush Rai
2019	J	`jnl`	Stochastic Blockmodels meet Graph Neural Networks. CoRR Nikhil Mehta, Lawrence Carin, Piyush Rai
2019	J	`jnl`	Variational Autoencoders for Sparse and Overdispersed Discrete Data. CoRR He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Mingyuan Zhou
2018	A*	`conf`	A Deep Generative Framework for Paraphrase Generation. AAAI Ankush Gupta, Arvind Agarwal, Prawaan Singh, Piyush Rai
2018	A	`conf`	A Generative Approach to Zero-Shot and Few-Shot Action Recognition. WACV Ashish Mishra, Vinay Kumar Verma, M. Shiva Krishna Reddy, Arulkumar Subramaniam, Piyush Rai, Anurag Mittal
2018	J	`jnl`	A Generative Approach to Zero-Shot and Few-Shot Action Recognition. CoRR Ashish Mishra, Vinay Kumar Verma, M. Shiva Krishna Reddy, Arulkumar Subramaniam, Piyush Rai, Anurag Mittal
2018	A	`conf`	Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. AISTATS He Zhao, Piyush Rai, Lan Du, Wray L. Buntine
2018	A*	`conf`	Generalized Zero-Shot Learning via Synthesized Examples. CVPR Vinay Kumar Verma, Gundeep Arora, Ashish Mishra, Piyush Rai
2018	J	`jnl`	Graph Convolutional Networks based Word Embeddings. CoRR Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar
2018	J	`jnl`	Leveraging Filter Correlations for Deep Model Compression. CoRR Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri
2018	A*	`conf`	Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels. IJCAI Gundeep Arora, Anupreet Porwal, Kanupriya Agarwal, Avani Samdariya, Piyush Rai
2018	J	`jnl`	Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels. CoRR Gundeep Arora, Anupreet Porwal, Kanupriya Agarwal, Avani Samdariya, Piyush Rai
2018	A*	`conf`	Zero-Shot Learning via Class-Conditioned Deep Generative Models. AAAI Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin
2017	J	`jnl`	A Deep Generative Framework for Paraphrase Generation. CoRR Ankush Gupta, Arvind Agarwal, Prawaan Singh, Piyush Rai
2017	A	`conf`	A Probabilistic Framework for Multi-Label Learning with Unseen Labels. UAI Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai
2017	—	`conf`	A Simple Exponential Family Framework for Zero-Shot Learning. ECML/PKDD (2) Vinay Kumar Verma, Piyush Rai
2017	J	`jnl`	A Simple Exponential Family Framework for Zero-Shot Learning. CoRR Vinay Kumar Verma, Piyush Rai
2017	A*	`conf`	Deep Generative Models for Relational Data with Side Information. ICML Changwei Hu, Piyush Rai, Lawrence Carin
2017	J	`jnl`	Generalized Zero-Shot Learning via Synthesized Examples. CoRR Gundeep Arora, Vinay Kumar Verma, Ashish Mishra, Piyush Rai
2017	J	`jnl`	Leveraging Distributional Semantics for Multi-Label Learning. CoRR Rahul Wadbude, Vivek Gupta, Piyush Rai, Nagarajan Natarajan, Harish Karnick
2017	A*	`conf`	Non-Negative Inductive Matrix Completion for Discrete Dyadic Data. AAAI Piyush Rai
2017	A*	`conf`	Scalable Generative Models for Multi-label Learning with Missing Labels. ICML Vikas Jain, Nirbhay Modhe, Piyush Rai
2017	J	`jnl`	Zero-Shot Learning via Class-Conditioned Deep Generative Models. CoRR Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin
2016	A*	`conf`	Architecture-Adaptive Code Variant Tuning. ASPLOS Saurav Muralidharan, Amit Roy, Mary W. Hall, Michael Garland, Piyush Rai
2016	—	`conf`	Deep Metric Learning with Data Summarization. ECML/PKDD (1) Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin
2016	J	`jnl`	Earliness-Aware Deep Convolutional Networks for Early Time Series Classification. CoRR Wenlin Wang, Changyou Chen, Wenqi Wang, Piyush Rai, Lawrence Carin
2016	A	`conf`	Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information. AISTATS Changwei Hu, Piyush Rai, Lawrence Carin
2016	A	`conf`	Topic-Based Embeddings for Learning from Large Knowledge Graphs. AISTATS Changwei Hu, Piyush Rai, Lawrence Carin
2015	A*	`conf`	Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision. AAAI Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin
2015	A*	`conf`	Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data. AAAI Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin
2015	—	`conf`	Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. NIPS Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin
2015	A*	`conf`	Leveraging Features and Networks for Probabilistic Tensor Decomposition. AAAI Piyush Rai, Yingjian Wang, Lawrence Carin
2015	J	`jnl`	Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data. CoRR Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin
2015	—	`conf`	Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data. ECML/PKDD (2) Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin
2015	A*	`conf`	Scalable Probabilistic Tensor Factorization for Binary and Count Data. IJCAI Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin
2015	A	`conf`	Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. UAI Changwei Hu, Piyush Rai, Lawrence Carin
2015	J	`jnl`	Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. CoRR Changwei Hu, Piyush Rai, Lawrence Carin
2014	A*	`conf`	Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. ICML Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David B. Dunson, Lawrence Carin
2013	—	`—`	Learning Latent Structures Via Bayesian Nonparametrics: New Models and Efficient Interference. Piyush Rai
2013	A*	`conf`	Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing. ICDM Joyce Jiyoung Whang, Piyush Rai, Inderjit S. Dhillon
2012	A*	`conf`	Flexible Modeling of Latent Task Structures in Multitask Learning. ICML Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daumé III
2012	J	`jnl`	Leveraging Social Bookmarks from Partially Tagged Corpus for Improved Web Page Clustering. ACM Trans. Intell. Syst. Technol. Anusua Trivedi, Piyush Rai, Hal Daumé III, Scott L. DuVall
2012	—	`conf`	Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression. NIPS Piyush Rai, Abhishek Kumar, Hal Daumé III
2011	—	`conf`	Active Supervised Domain Adaptation. ECML/PKDD (3) Avishek Saha, Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian, Scott L. DuVall
2011	A*	`conf`	Beam Search based MAP Estimates for the Indian Buffet Process. ICML Piyush Rai, Hal Daumé III
2011	—	`conf`	Co-regularized Multi-view Spectral Clustering. NIPS Abhishek Kumar, Piyush Rai, Hal Daumé III
2011	A*	`conf`	Distinguishing locations across perimeters using wireless link measurements. INFOCOM Junxing Zhang, Sneha Kumar Kasera, Neal Patwari, Piyush Rai
2011	—	`conf`	Message-Passing for Approximate MAP Inference with Latent Variables. NIPS Jiarong Jiang, Piyush Rai, Hal Daumé III
2011	A	`conf`	Online Learning of Multiple Tasks and Their Relationships. AISTATS Avishek Saha, Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian
2011	—	`conf`	Video Scene Segmentation with a Semantic Similarity. IICAI Niraj Kumar, Piyush Rai, Chandrika Pulla, C. V. Jawahar
2010	—	`conf`	Exploiting tag and word correlations for improved webpage clustering. SMUC@CIKM Anusua Trivedi, Piyush Rai, Scott L. DuVall, Hal Daumé III
2010	A	`conf`	Infinite Predictor Subspace Models for Multitask Learning. AISTATS Piyush Rai, Hal Daumé III
2009	—	`conf`	Multi-Label Prediction via Sparse Infinite CCA. NIPS Piyush Rai, Hal Daumé III
2009	J	`jnl`	Streamed Learning: One-Pass SVMs CoRR Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian
2009	A*	`conf`	Streamed Learning: One-Pass SVMs. IJCAI Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian
2009	J	`jnl`	The Infinite Hierarchical Factor Regression Model CoRR Piyush Rai, Hal Daumé III
2008	—	`conf`	The Infinite Hierarchical Factor Regression Model. NIPS Piyush Rai, Hal Daumé III