163 citations · 397 across the 26 of their papers we have counts for
5 papers · 1 filter
Cluster-and-Conquer: A Framework For Time-Series Forecasting
Reese Pathak, Rajat Sen, Nikhil Rao +3
We propose a three-stage framework for forecasting high-dimensional time-series data. Our method first estimates parameters for each univariate time series. Next, we use these para…
Bandits with Stochastic Experts: Constant Regret, Empirical Experts and Episodes
Nihal Sharma, Rajat Sen, Soumya Basu +2
We study a variant of the contextual bandit problem where an agent can intervene through a set of stochastic expert policies. Given a fixed context, each expert samples actions fro…
On the benefits of maximum likelihood estimation for Regression and Forecasting
Pranjal Awasthi, Abhimanyu Das, Rajat Sen +1
We advocate for a practical Maximum Likelihood Estimation (MLE) approach towards designing loss functions for regression and forecasting, as an alternative to the typical approach…
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…
Top- eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying +4
Motivated by modern applications, such as online advertisement and recommender systems, we study the top- extreme contextual bandits problem, where the total number of arms can…