178 citations · 289 across the 10 of their papers we have counts for
6 papers · 1 filter
Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting
Abhimanyu Das, Weihao Kong, Biswajit Paria +1
Probabilistic, hierarchically coherent forecasting is a key problem in many practical forecasting applications -- the goal is to obtain coherent probabilistic predictions for a lar…
An Experimental Design Perspective on Model-Based Reinforcement Learning
Viraj Mehta, Biswajit Paria, Jeff Schneider +2
In many practical applications of RL, it is expensive to observe state transitions from the environment. For example, in the problem of plasma control for nuclear fusion, computing…
Hierarchically Regularized Deep Forecasting
Biswajit Paria, Rajat Sen, Amr Ahmed +1
Hierarchical forecasting is a key problem in many practical multivariate forecasting applications - the goal is to simultaneously predict a large number of correlated time series t…
Minimizing FLOPs to Learn Efficient Sparse Representations
Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen +3
Deep representation learning has become one of the most widely adopted approaches for visual search, recommendation, and identification. Retrieval of such representations from a la…
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations
Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
Many real world applications can be framed as multi-objective optimization problems, where we wish to simultaneously optimize for multiple criteria. Bayesian optimization technique…
Forward Stagewise Additive Model for Collaborative Multiview Boosting
Avisek Lahiri, Biswajit Paria, Prabir Kumar Biswas
Multiview assisted learning has gained significant attention in recent years in supervised learning genre. Availability of high performance computing devices enables learning algor…