1 citations · 1 across the 13 of their papers we have counts for
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Forecasting from Counterfactual Simulator Rollouts: A Sim2Real Evaluation
Angel Wang, Dominique Perrault-Joncas, Alvaro Maggiar +2
Deploying a new decision policy creates a cold-start problem for prediction models whose targets depend on the policy's actions: historical observations reflect earlier policies, w…
Proximal Residual Value Functions for Consistent Planning and Real-Time Execution
Harrison Waldon, Carson Eisenach, Akhil Bagaria +4
We study two-timescale decision systems in which a planning layer periodically supplies a continuation-value function to a real-time optimizer that allocates arriving resources, wi…
BRIDGE: Building Representations In Domain Guided Program Synthesis
Robert Joseph George, Carson Eisenach, Udaya Ghai +3
Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalability challenge is that verified syn…
Structure-Informed Deep Reinforcement Learning for Inventory Management
Alvaro Maggiar, Sohrab Andaz, Akhil Bagaria +4
This paper investigates the application of Deep Reinforcement Learning (DRL) to classical inventory management problems, with a focus on practical implementation considerations. We…
Outbound Modeling for Inventory Management
Riccardo Savorgnan, Udaya Ghai, Carson Eisenach +1
We study the problem of forecasting the number of units fulfilled (or ``drained'') from each inventory warehouse to meet customer demand, along with the associated outbound shippin…
How Does Critical Batch Size Scale in Pre-training?
Hanlin Zhang, Depen Morwani, Nikhil Vyas +5
Training large-scale models under given resources requires careful design of parallelism strategies. In particular, the efficiency notion of critical batch size (CBS), concerning t…
Learning an Inventory Control Policy with General Inventory Arrival Dynamics
Sohrab Andaz, Carson Eisenach, Dhruv Madeka +4
In this paper we address the problem of learning and backtesting inventory control policies in the presence of general arrival dynamics -- which we term as a quantity-over-time arr…