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Constrained Sampling from Language Models via Langevin Dynamics in Embedding Spaces


May 25, 2022
Sachin Kumar, Biswajit Paria, Yulia Tsvetkov


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A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting


Apr 21, 2022
Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen


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An Experimental Design Perspective on Model-Based Reinforcement Learning


Dec 09, 2021
Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger


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Hierarchically Regularized Deep Forecasting


Jun 14, 2021
Biswajit Paria, Rajat Sen, Amr Ahmed, Abhimanyu Das


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Minimizing FLOPs to Learn Efficient Sparse Representations


Apr 12, 2020
Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen, Ning Xu, Pradeep Ravikumar, Barnab谩s P贸czos

* Published at ICLR 2020 

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Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly


Mar 15, 2019
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabas Poczos, Eric P. Xing


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A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations


Oct 22, 2018
Biswajit Paria, Kirthevasan Kandasamy, Barnab谩s P贸czos


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A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference


Jan 27, 2017
Biswajit Paria, K. M. Annervaz, Ambedkar Dukkipati, Ankush Chatterjee, Sanjay Podder

* 8 pages, 2 figures 

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Visualization Regularizers for Neural Network based Image Recognition


Jan 03, 2017
Biswajit Paria, Vikas Reddy, Anirban Santara, Pabitra Mitra


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Forward Stagewise Additive Model for Collaborative Multiview Boosting


Aug 05, 2016
Avisek Lahiri, Biswajit Paria, Prabir Kumar Biswas

* The manuscript is currently under "Minor Revision" at IEEE Transactions on Neural Networks and Learning Systems 

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