Rectification-Based Knowledge Retention for Task Incremental Learning - Pratik Mazumder; Pravendra Singh; Piyush Rai; Vinay P. Namboodiri (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Text-Based Fine-Grained Emotion Prediction - Gargi Singh; Dhanajit Brahma; Piyush Rai; Ashutosh Modi (IEEE Trans. Affect. Comput., 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 (IEEE International Conference on Robotics and Automation, ICRA 2024, Yokohama, Japan, May 13-17, 2024, 2024)

Robust Black-box Testing of Deep Neural Networks using Co-Domain Coverage - Aishwarya Gupta; Indranil Saha; Piyush Rai (CoRR, 2024)

RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance - Avideep Mukherjee; Soumya Banerjee; Vinay P. Namboodiri; Piyush Rai (CoRR, 2024)

Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization - Shivam Pal; Aishwarya Gupta; Saqib Sarwar; Piyush Rai (CoRR, 2024)

Spatio-Temporal Forecasting of PM2.5 via Spatial-Diffusion guided Encoder-Decoder Architecture - Malay Pandey; Vaishali Jain; Nimit Godhani; Sachchida Nand Tripathi; Piyush Rai (CoRR, 2024)

Federated Learning with Uncertainty via Distilled Predictive Distributions - Shrey Bhatt; Aishwarya Gupta; Piyush Rai (Asian Conference on Machine Learning, ACML 2023, 11-14 November 2023, Istanbul, Turkey, 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), Mumbai, India, January 4-7, 2023, 2023)

A Probabilistic Framework for Lifelong Test-Time Adaptation - Dhanajit Brahma; Piyush Rai (IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023, 2023)

VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference - Soumya Banerjee; Vinay Kumar Verma; Avideep Mukherjee; Deepak Gupta; Vinay P. Namboodiri; Piyush Rai (CoRR, 2023)

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents - Kushagra Pandey; Avideep Mukherjee; Piyush Rai; Abhishek Kumar (Trans. Mach. Learn. Res., 2022)

Spacing Loss for Discovering Novel Categories - K. J. Joseph; Sujoy Paul; Gaurav Aggarwal; Soma Biswas; Piyush Rai; Kai Han; Vineeth N. Balasubramanian (IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2022, New Orleans, LA, USA, June 19-20, 2022, 2022)

Novel Class Discovery Without Forgetting - K. J. Joseph; Sujoy Paul; Gaurav Aggarwal; Soma Biswas; Piyush Rai; Kai Han; Vineeth N. Balasubramanian (Computer Vision - ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXIV, 2022)

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents - Kushagra Pandey; Avideep Mukherjee; Piyush Rai; Abhishek Kumar (CoRR, 2022)

Semi-Supervised Super-Resolution - Ankur Singh; Piyush Rai (CoRR, 2022)

Spacing Loss for Discovering Novel Categories - K. J. Joseph; Sujoy Paul; Gaurav Aggarwal; Soma Biswas; Piyush Rai; Kai Han; Vineeth N. Balasubramanian (CoRR, 2022)

Bayesian Federated Learning via Predictive Distribution Distillation - Shrey Bhatt; Aishwarya Gupta; 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 (CoRR, 2022)

A Probabilistic Framework for Lifelong Test-Time Adaptation - Dhanajit Brahma; Piyush Rai (CoRR, 2022)

Few-Shot Lifelong Learning - Pratik Mazumder; Pravendra Singh; Piyush Rai (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

Generalized Adversarially Learned Inference - Yatin Dandi; Homanga Bharadhwaj; Abhishek Kumar; Piyush Rai (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

Fine-Grained Emotion Prediction by Modeling Emotion Definitions - Gargi Singh; Dhanajit Brahma; Piyush Rai; Ashutosh Modi (9th International Conference on Affective Computing and Intelligent Interaction, ACII 2021, Nara, Japan, September 28 - Oct. 1, 2021, 2021)

Efficient Feature Transformations for Discriminative and Generative Continual Learning - Vinay Kumar Verma; Kevin J. Liang; Nikhil Mehta; Piyush Rai; Lawrence Carin (IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021, 2021)

Rectification-Based Knowledge Retention for Continual Learning - Pravendra Singh; Pratik Mazumder; Piyush Rai; Vinay P. Namboodiri (IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021, 2021)

Bayesian Structural Adaptation for Continual Learning - Abhishek Kumar; Sunabha Chatterjee; Piyush Rai (Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, 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, IJCAI 2021, Virtual Event / Montreal, Canada, 19-27 August 2021, 2021)

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks - Sakshi Varshney; Vinay Kumar Verma; P. K. Srijith; Lawrence Carin; Piyush Rai (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Towards Zero-Shot Learning with Fewer Seen Class Examples - Vinay Kumar Verma; Ashish Mishra; Anubha Pandey; Hema A. Murthy; Piyush Rai (IEEE Winter Conference on Applications of Computer Vision, WACV 2021, Waikoloa, HI, USA, January 3-8, 2021, 2021)

Few-Shot Lifelong Learning - Pratik Mazumder; Pravendra Singh; Piyush Rai (CoRR, 2021)

Efficient Continual Adaptation for Generative Adversarial Networks - Sakshi Varshney; Vinay Kumar Verma; Lawrence Carin; Piyush Rai (CoRR, 2021)

Efficient Feature Transformations for Discriminative and Generative Continual Learning - Vinay Kumar Verma; Kevin J. Liang; Nikhil Mehta; Piyush Rai; Lawrence Carin (CoRR, 2021)

Variational Rejection Particle Filtering - Rahul Sharma; Soumya Banerjee; Dootika Vats; Piyush Rai (CoRR, 2021)

Rectification-based Knowledge Retention for Continual Learning - Pravendra Singh; Pratik Mazumder; Piyush Rai; Vinay P. Namboodiri (CoRR, 2021)

Knowledge Consolidation based Class Incremental Online Learning with Limited Data - Mohammed Asad Karim; Vinay Kumar Verma; Pravendra Singh; Vinay P. Namboodiri; Piyush Rai (CoRR, 2021)

Fine-Grained Emotion Prediction by Modeling Emotion Definitions - Gargi Singh; Dhanajit Brahma; Piyush Rai; Ashutosh Modi (CoRR, 2021)

Hypernetworks for Continual Semi-Supervised Learning - Dhanajit Brahma; Vinay Kumar Verma; Piyush Rai (CoRR, 2021)

NeurInt : Learning to Interpolate through Neural ODEs - Avinandan Bose; Aniket Das; Yatin Dandi; Piyush Rai (CoRR, 2021)

SITA: Single Image Test-time Adaptation - Ansh Khurana; Sujoy Paul; Piyush Rai; Soma Biswas; Gaurav Aggarwal (CoRR, 2021)

HetConv: Beyond Homogeneous Convolution Kernels for Deep CNNs - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (Int. J. Comput. Vis., 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)

Graph Representation Learning via Ladder Gamma Variational Autoencoders - Arindam Sarkar; Nikhil Mehta; Piyush Rai (The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 2020)

Meta-Learning for Generalized Zero-Shot Learning - Vinay Kumar Verma; Dhanajit Brahma; Piyush Rai (The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 2020)

P-SIF: Document Embeddings Using Partition Averaging - Vivek Gupta; Ankit Saw; Pegah Nokhiz; Praneeth Netrapalli; Piyush Rai; Partha P. Talukdar (The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 2020)

Deep Attentive Ranking Networks for Learning to Order Sentences - Pawan Kumar; Dhanajit Brahma; Harish Karnick; Piyush Rai (The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 2020)

Variational Autoencoders for Sparse and Overdispersed Discrete Data - He Zhao; Piyush Rai; Lan Du; Wray L. Buntine; Dinh Phung; Mingyuan Zhou (The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], 2020)

Calibrating CNNs for Lifelong Learning - Pravendra Singh; Vinay Kumar Verma; Pratik Mazumder; Lawrence Carin; Piyush Rai (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Leveraging Filter Correlations for Deep Model Compression - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 2020)

A "Network Pruning Network" Approach to Deep Model Compression - Vinay Kumar Verma; Pravendra Singh; Vinay P. Namboodiri; Piyush Rai (IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 2020)

Jointly Trained Image and Video Generation using Residual Vectors - Yatin Dandi; Aniket Das; Soumye Singhal; Vinay P. Namboodiri; Piyush Rai (IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 2020)

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation - Varun Khare; Divyat Mahajan; Homanga Bharadhwaj; Vinay Kumar Verma; Piyush Rai (IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 2020)

Deep Attentive Ranking Networks for Learning to Order Sentences - Pawan Kumar; Dhanajit Brahma; Harish Karnick; Piyush Rai (CoRR, 2020)

A "Network Pruning Network" Approach to Deep Model Compression - Vinay Kumar Verma; Pravendra Singh; Vinay P. Namboodiri; Piyush Rai (CoRR, 2020)

Quantile Regularization: Towards Implicit Calibration of Regression Models - Saiteja Utpala; Piyush Rai (CoRR, 2020)

P-SIF: Document Embeddings Using Partition Averaging - Vivek Gupta; Ankit Saw; Pegah Nokhiz; Praneeth Netrapalli; Piyush Rai; Partha P. Talukdar (CoRR, 2020)

Generalized Adversarially Learned Inference - Yatin Dandi; Homanga Bharadhwaj; Abhishek Kumar; Piyush Rai (CoRR, 2020)

Towards Zero-Shot Learning with Fewer Seen Class Examples - Vinay Kumar Verma; Ashish Mishra; Anubha Pandey; Hema A. Murthy; Piyush Rai (CoRR, 2020)

A flexible probabilistic framework for large-margin mixture of experts - Archit Sharma; Siddhartha Saxena; Piyush Rai (Mach. Learn., 2019)

Distributional Semantics Meets Multi-Label Learning - Vivek Gupta; Rahul Wadbude; Nagarajan Natarajan; Harish Karnick; Prateek Jain; Piyush Rai (The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, 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, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers, 2019)

Deep Topic Models for Multi-label Learning - Rajat Panda; Ankit Pensia; Nikhil Mehta; Mingyuan Zhou; Piyush Rai (The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, 2019)

Generative Model for Zero-Shot Sketch-Based Image Retrieval - Vinay Kumar Verma; Aakansha Mishra; Ashish Mishra; Piyush Rai (IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2019, Long Beach, CA, USA, June 16-20, 2019, 2019)

HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019, 2019)

Stochastic Blockmodels meet Graph Neural Networks - Nikhil Mehta; Lawrence Carin; Piyush Rai (Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, 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, IJCAI 2019, Macao, China, August 10-16, 2019, 2019)

HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (CoRR, 2019)

Generative Model for Zero-Shot Sketch-Based Image Retrieval - Vinay Kumar Verma; Aakansha Mishra; Ashish Mishra; 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 (CoRR, 2019)

Stochastic Blockmodels meet Graph Neural Networks - Nikhil Mehta; Lawrence Carin; Piyush Rai (CoRR, 2019)

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation - Varun Khare; Divyat Mahajan; Homanga Bharadhwaj; Vinay Kumar Verma; Piyush Rai (CoRR, 2019)

A Meta-Learning Framework for Generalized Zero-Shot Learning - Vinay Kumar Verma; Dhanajit Brahma; Piyush Rai (CoRR, 2019)

Refined \(α\)-Divergence Variational Inference via Rejection Sampling - Rahul Sharma; Abhishek Kumar; Piyush Rai (CoRR, 2019)

Nonparametric Bayesian Structure Adaptation for Continual Learning - Abhishek Kumar; Sunabha Chatterjee; Piyush Rai (CoRR, 2019)

On the relationship between multitask neural networks and multitask Gaussian Processes - Karthikeyan K; Shubham Kumar Bharti; Piyush Rai (CoRR, 2019)

Jointly Trained Image and Video Generation using Residual Vectors - Yatin Dandi; Aniket Das; Soumye Singhal; Vinay P. Namboodiri; Piyush Rai (CoRR, 2019)

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, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 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, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 2018)

Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences - He Zhao; Piyush Rai; Lan Du; Wray L. Buntine (International Conference on Artificial Intelligence and Statistics, AISTATS 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, Spain, 2018)

Generalized Zero-Shot Learning via Synthesized Examples - Vinay Kumar Verma; Gundeep Arora; Ashish Mishra; Piyush Rai (2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18-22, 2018, 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, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden, 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 (2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018, Lake Tahoe, NV, USA, March 12-15, 2018, 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 (CoRR, 2018)

Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels - Gundeep Arora; Anupreet Porwal; Kanupriya Agarwal; Avani Samdariya; Piyush Rai (CoRR, 2018)

Graph Convolutional Networks based Word Embeddings - Shikhar Vashishth; Prateek Yadav; Manik Bhandari; Piyush Rai; Chiranjib Bhattacharyya; Partha P. Talukdar (CoRR, 2018)

Leveraging Filter Correlations for Deep Model Compression - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (CoRR, 2018)

Non-Negative Inductive Matrix Completion for Discrete Dyadic Data - Piyush Rai (Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA, 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, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, 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, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, 2017)

A Simple Exponential Family Framework for Zero-Shot Learning - Vinay Kumar Verma; Piyush Rai (Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II, 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, UAI 2017, Sydney, Australia, August 11-15, 2017, 2017)

A Simple Exponential Family Framework for Zero-Shot Learning - Vinay Kumar Verma; Piyush Rai (CoRR, 2017)

A Deep Generative Framework for Paraphrase Generation - Ankush Gupta; Arvind Agarwal; Prawaan Singh; Piyush Rai (CoRR, 2017)

Leveraging Distributional Semantics for Multi-Label Learning - Rahul Wadbude; Vivek Gupta; Piyush Rai; Nagarajan Natarajan; Harish Karnick (CoRR, 2017)

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 (CoRR, 2017)

Generalized Zero-Shot Learning via Synthesized Examples - Gundeep Arora; Vinay Kumar Verma; Ashish Mishra; Piyush Rai (CoRR, 2017)

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, AISTATS 2016, Cadiz, Spain, May 9-11, 2016, 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, AISTATS 2016, Cadiz, Spain, May 9-11, 2016, 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, ASPLOS 2016, Atlanta, GA, USA, April 2-6, 2016, 2016)

Deep Metric Learning with Data Summarization - Wenlin Wang; Changyou Chen; Wenlin Chen; Piyush Rai; Lawrence Carin (Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I, 2016)

Earliness-Aware Deep Convolutional Networks for Early Time Series Classification - Wenlin Wang; Changyou Chen; Wenqi Wang; Piyush Rai; Lawrence Carin (CoRR, 2016)

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, January 25-30, 2015, Austin, Texas, USA, 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, January 25-30, 2015, Austin, Texas, USA, 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, January 25-30, 2015, Austin, Texas, USA, 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, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015, 2015)

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings - Piyush Rai; Changwei Hu; Ricardo Henao; Lawrence Carin (Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, 2015)

Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data - Changwei Hu; Piyush Rai; Changyou Chen; Matthew Harding; Lawrence Carin (Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II, 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, UAI 2015, July 12-16, 2015, Amsterdam, The Netherlands, 2015)

Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors - Changwei Hu; Piyush Rai; Lawrence Carin (CoRR, 2015)

Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data - Changwei Hu; Piyush Rai; Changyou Chen; Matthew Harding; Lawrence Carin (CoRR, 2015)

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, ICML 2014, Beijing, China, 21-26 June 2014, 2014)

Learning Latent Structures Via Bayesian Nonparametrics: New Models and Efficient Interference - Piyush Rai (University of Utah, USA, 2013)

Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing - Joyce Jiyoung Whang; Piyush Rai; Inderjit S. Dhillon (2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013, 2013)

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)

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, ICML 2012, Edinburgh, Scotland, UK, June 26 - July 1, 2012, 2012)

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression - Piyush Rai; Abhishek Kumar; Hal Daumé III (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, Lake Tahoe, Nevada, United States, 2012)

Beam Search based MAP Estimates for the Indian Buffet Process - Piyush Rai; Hal Daumé III (Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011, 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, IICAI 2011, Tumkur, Karnataka State, India, December 14-16, 2011, 2011)

Distinguishing locations across perimeters using wireless link measurements - Junxing Zhang; Sneha Kumar Kasera; Neal Patwari; Piyush Rai (INFOCOM 2011. 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 10-15 April 2011, Shanghai, China, 2011)

Message-Passing for Approximate MAP Inference with Latent Variables - Jiarong Jiang; Piyush Rai; Hal Daumé III (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, Granada, Spain, 2011)

Co-regularized Multi-view Spectral Clustering - Abhishek Kumar; Piyush Rai; Hal Daumé III (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, Granada, Spain, 2011)

Active Supervised Domain Adaptation - Avishek Saha; Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian; Scott L. DuVall (Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III, 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, AISTATS 2011, Fort Lauderdale, USA, April 11-13, 2011, 2011)

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, SMUC@CIKM 2010, Toronto, ON, Canada, October 30, 2010, 2010)

Infinite Predictor Subspace Models for Multitask Learning - Piyush Rai; Hal Daumé III (Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15, 2010, 2010)

Streamed Learning: One-Pass SVMs - Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian (IJCAI 2009, Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, July 11-17, 2009, 2009)

Multi-Label Prediction via Sparse Infinite CCA - Piyush Rai; Hal Daumé III (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, Vancouver, British Columbia, Canada, 2009)

The Infinite Hierarchical Factor Regression Model - Piyush Rai; Hal Daumé III (CoRR, 2009)

Streamed Learning: One-Pass SVMs - Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian (CoRR, 2009)

The Infinite Hierarchical Factor Regression Model - Piyush Rai; Hal Daumé III (Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008, 2008)