5 papers · 1 filter
Aligning Learning and Endogenous Decision-Making
Rares Cristian, Pavithra Harsha, Georgia Perakis +1
Many of the observations we make are biased by our decisions. For instance, the demand of items is impacted by the prices set, and online checkout choices are influenced by the ass…
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach
Rares Cristian, Pavithra Harsha, Georgia Perakis +1
End-to-end learning has become a widely applicable and studied problem in training predictive ML models to be aware of their impact on downstream decision-making tasks. These end-t…
CoRe: Coherency Regularization for Hierarchical Time Series
Rares Cristian, Pavithra Harhsa, Georgia Perakis +1
Hierarchical time series forecasting presents unique challenges, particularly when dealing with noisy data that may not perfectly adhere to aggregation constraints. This paper intr…
Deep Policy Iteration with Integer Programming for Inventory Management
Pavithra Harsha, Ashish Jagmohan, Jayant Kalagnanam +2
We present a Reinforcement Learning (RL) based framework for optimizing long-term discounted reward problems with large combinatorial action space and state dependent constraints.…
Inter-Series Transformer: Attending to Products in Time Series Forecasting
Rares Cristian, Pavithra Harsha, Clemente Ocejo +4
Time series forecasting is an important task in many fields ranging from supply chain management to weather forecasting. Recently, Transformer neural network architectures have sho…