Biswajit Paria

23 papers A* 3A 2Journal 14Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	A	`conf`	Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. UAI Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
2022	J	`jnl`	A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. CoRR Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
2022	A*	`conf`	An Experimental Design Perspective on Model-Based Reinforcement Learning. ICLR Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger
2022	J	`jnl`	Constrained Sampling from Language Models via Langevin Dynamics in Embedding Spaces. CoRR Sachin Kumar, Biswajit Paria, Yulia Tsvetkov
2022	A*	`conf`	Gradient-based Constrained Sampling from Language Models. EMNLP Sachin Kumar, Biswajit Paria, Yulia Tsvetkov
2022	—	`—`	Strategies for Black-Box and Multi-Objective Optimization Biswajit Paria
2021	J	`jnl`	An Experimental Design Perspective on Model-Based Reinforcement Learning. CoRR Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger
2021	J	`jnl`	Hierarchically Regularized Deep Forecasting. CoRR Biswajit Paria, Rajat Sen, Amr Ahmed, Abhimanyu Das
2020	J	`jnl`	Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning. CoRR Adarsh Dave, Jared Mitchell, Kirthevasan Kandasamy, Sven Burke, Biswajit Paria, Barnabás Póczos, Jay Whitacre, Venkatasubramanian Viswanathan
2020	A*	`conf`	Minimizing FLOPs to Learn Efficient Sparse Representations. ICLR Biswajit Paria, Chih-Kuan Yeh, Ian En-Hsu Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos
2020	J	`jnl`	Minimizing FLOPs to Learn Efficient Sparse Representations. CoRR Biswajit Paria, Chih-Kuan Yeh, Ian En-Hsu Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos
2020	J	`jnl`	Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. J. Mach. Learn. Res. Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing
2019	A	`conf`	A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations. UAI Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
2019	J	`jnl`	Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. CoRR Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing
2018	J	`jnl`	A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations. CoRR Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
2018	J	`jnl`	Forward Stagewise Additive Model for Collaborative Multiview Boosting. IEEE Trans. Neural Networks Learn. Syst. Avisek Lahiri, Biswajit Paria, Prabir Kumar Biswas
2017	J	`jnl`	Analytic Connectivity in General Hypergraphs. CoRR Ashwin Guha, Muni Sreenivas Pydi, Biswajit Paria, Ambedkar Dukkipati
2017	—	`conf`	PolicyGAN: Training generative adversarial networks using policy gradient. ICAPR Biswajit Paria, Avisek Lahiri, Prabir Kumar Biswas
2016	J	`jnl`	A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference. CoRR Biswajit Paria, K. M. Annervaz, Ambedkar Dukkipati, Ankush Chatterjee, Sanjay Podder
2016	—	`conf`	COMA-boost: co-operative multi agent AdaBoost. ICVGIP Avisek Lahiri, Biswajit Paria, Prabir Kumar Biswas
2016	J	`jnl`	Forward Stagewise Additive Model for Collaborative Multiview Boosting. CoRR Avisek Lahiri, Biswajit Paria, Prabir Kumar Biswas
2016	J	`jnl`	Visualization Regularizers for Neural Network based Image Recognition. CoRR Biswajit Paria, Anirban Santara, Pabitra Mitra
2015	—	`conf`	On the broadcast of segmented messages in dynamic networks. INFOCOM Workshops Sandipan Sikdar, Marcin Bodych, Rajib Ranjan Maiti, Biswajit Paria, Niloy Ganguly, Tyll Krueger, Animesh Mukherjee